diff --git a/CRAN-RELEASE b/CRAN-RELEASE new file mode 100644 index 0000000..67f9346 --- /dev/null +++ b/CRAN-RELEASE @@ -0,0 +1,2 @@ +This package was submitted to CRAN on 2019-09-19. +Once it is accepted, delete this file and tag the release (commit 700fe92dfa). diff --git a/DESCRIPTION b/DESCRIPTION index 2ad367c..0c1eca0 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,7 +1,7 @@ Package: tibbletime Type: Package Title: Time Aware Tibbles -Version: 0.1.2.9000 +Version: 0.1.3 Authors@R: c( person("Davis", "Vaughan", email = "davis@rstudio.com", role = c("aut", "cre")), person("Matt", "Dancho", email = "mdancho@business-science.io", role = c("aut")) diff --git a/NEWS.md b/NEWS.md index 3b4f01d..6d1bb36 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,4 +1,4 @@ -# tibbletime (development version) +# tibbletime 0.1.3 * Features diff --git a/cran-comments.md b/cran-comments.md index 0c60f62..aeffde9 100644 --- a/cran-comments.md +++ b/cran-comments.md @@ -1,19 +1,11 @@ -## Resubmission - -I accidentally shipped the entire revdep/ folder alongside the package. I have -added it to '.Rbuildignore' now. - ## Release Summary -This is a minor release of 'tibbletime'. It fixes a few small bugs regarding -the new version of 'tibble', and changes a test in preparation for -'dplyr' 0.8.0. - -I have also changed the maintainer email to reflect a job change. +This is a minor release of 'tibbletime'. It mainly updates the `tidyr::nest()` +and `tidyr::unnest()` methods for compatability with tidyr 1.0.0. ## Test environments -* local Mac install, R 3.5.1 -* ubuntu 14.04.5 (on travis-ci) (3.4.4, devel, release) +* local Mac install, R 3.6.0 +* ubuntu 14.04.5 (on travis-ci) (3.6.0, devel, release) * win-builder (devel and release) ## R CMD check results @@ -27,13 +19,6 @@ There were no ERRORs, WARNINGs or NOTEs. ## Revdep checks -The 3 reverse dependencies passed with no errors, and the warnings / notes -were unrelated to this update. - -|package |version |error |warning |note | -|:----------------------------------|:-------|:-----|:-------|:----| -|[anomalize](problems.md#anomalize) |0.1.1 | | |1 | -|[tidyquant](problems.md#tidyquant) |0.5.5 | |1 | | -|tsbox |0.0.3 | | | | - +The 4 revdeps have been checked, and nothing has been broken by this release. +This should free up anomalize to be fixed as well (tidyr 1.0.0 broke it). diff --git a/docs/404.html b/docs/404.html new file mode 100644 index 0000000..2495874 --- /dev/null +++ b/docs/404.html @@ -0,0 +1,166 @@ + + + + + + + + +Page not found (404) • tibbletime + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + + +
+ +
+
+
+

Page not found (404)

+
+ +Content not found. Please use links in the navbar. + +
+ +
+ + + + +
+ + + + + + + + diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html index c117f1b..ebf2ff2 100644 --- a/docs/LICENSE-text.html +++ b/docs/LICENSE-text.html @@ -8,21 +8,25 @@ License • tibbletime + - + + - + - + + - + - - + + + @@ -30,12 +34,15 @@ + + - + + +
@@ -138,13 +146,14 @@

License

+ @@ -152,6 +161,8 @@

License

+ + diff --git a/docs/articles/TT-01-time-based-filtering.html b/docs/articles/TT-01-time-based-filtering.html index 7a861ad..5591a4d 100644 --- a/docs/articles/TT-01-time-based-filtering.html +++ b/docs/articles/TT-01-time-based-filtering.html @@ -6,13 +6,14 @@ Time-based filtering • tibbletime - - - + + + + - - - + + + + - - - + + + + - - - + + + + - - + + - + - + + - + - - + + + @@ -30,12 +34,15 @@ + + - + + +
@@ -143,13 +151,14 @@

All vignettes

+ @@ -157,6 +166,8 @@

All vignettes

+ + diff --git a/docs/authors.html b/docs/authors.html index c94eaba..1ccddaa 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -8,21 +8,25 @@ Authors • tibbletime + - + + - + - + + - + - - + + + @@ -30,12 +34,15 @@ + + - + + +
@@ -145,13 +153,14 @@

Authors

+ @@ -159,6 +168,8 @@

Authors

+ + diff --git a/docs/index.html b/docs/index.html index 0949842..5adbc80 100644 --- a/docs/index.html +++ b/docs/index.html @@ -6,17 +6,18 @@ Time Aware Tibbles • tibbletime - - - + + + + - + and creating columns that can be used as dplyr time-based groups."> - - + + - + - + + - + - - + + + @@ -30,12 +34,15 @@ + + - + + +
@@ -130,7 +138,26 @@

Changelog

Source: NEWS.md
-
+
+

+tibbletime (development version) Unreleased +

+ +

tibbletime 0.1.2

    @@ -145,13 +172,13 @@

    • For tibble 2.0.1, an internal bug fix was made to pass along an nrow argument.

    • For dplyr 0.8.0, an internal fix was made in one of the tests.

      • -

    • A new line was added to inst/include/is_ordered.h to appease CRAN.

      • -

    • The tbl_time time zone for POSIXct indices is now set as the first non NA value of: “tzone” attribute -> Sys.timezone() -> “UTC”. Previously there was no Sys.timezone() step as there were problems with local time zones such as America/New_York interacting with collapsing by day. Those problems have been fixed by using DSTday with all POSIXct indices even if day is specified.

      • +

    • A new line was added to inst/include/is_ordered.h to appease CRAN.

      • +

    • The tbl_time time zone for POSIXct indices is now set as the first non NA value of: “tzone” attribute -> Sys.timezone() -> “UTC”. Previously there was no Sys.timezone() step as there were problems with local time zones such as America/New_York interacting with collapsing by day. Those problems have been fixed by using DSTday with all POSIXct indices even if day is specified.

-
+

tibbletime 0.1.1

    @@ -175,7 +202,7 @@

-
+

tibbletime 0.1.0

This is a major update. It introduces a huge number of breaking changes as we heavily reworked the internals of the package. This should ensure the longevity of the package and provide maximum flexibility for its use with dplyr. As this was still early in package development with minimal usage, and because we had issued a Warning in the README of the last update that we may change things, we have not made any attempt to support backwards compatability. From this point forward, however, we will support backwards compatability as we feel that we have reached a more stable implementation.

@@ -184,8 +211,8 @@

  • General

      -

    • The period argument no longer supports the ‘period formula’ (e.g. 1~year). It added unnecessary complication with little benefit. Rather, a character should be used like '1 year'. See the documentation of partition_index() for full details.

      • -

    • time_formula arguments still support the from ~ to style syntax, but the left and right hand sides must now be characters, rather than bare date specifications. In English, rather than 2013 ~ 2014, you must use '2013' ~ '2014'. This is easier to program with and also allows you to pass in variables to the time formula, which previously did not work well.

      • +

    • The period argument no longer supports the ‘period formula’ (e.g. 1~year). It added unnecessary complication with little benefit. Rather, a character should be used like '1 year'. See the documentation of partition_index() for full details.

      • +

    • time_formula arguments still support the from ~ to style syntax, but the left and right hand sides must now be characters, rather than bare date specifications. In English, rather than 2013 ~ 2014, you must use '2013' ~ '2014'. This is easier to program with and also allows you to pass in variables to the time formula, which previously did not work well.

    • time_filter() has become filter_time(). This naming is easier to remember now that a suite of time_*() functions is not being developed and is easier to find with autocompletion.

    • time_group() and time_collapse() have become partition_index() and collapse_index(). Both functions accept index vectors and are commonly used inside dplyr::mutate().

    • partition_index() splits an index by period and returns an integer vector corresponding to the groups.

      • @@ -193,7 +220,7 @@

    • There is full support for Date and POSIXct classes as the index, and there is experimental support for yearmon, yearqtr, and hms classes.

    • ceiling_index() and floor_index() are thin wrappers around lubridate functions of similar names, but they also work for yearmon, yearqtr and hms.

    • create_series() now has an explicit class argument.

      • -

    • as_period() gains an include_endpoints argument for including the last data point if side = "start" is specified or the first data point if side = "end" is used.

      • +

    • as_period() gains an include_endpoints argument for including the last data point if side = "start" is specified or the first data point if side = "end" is used.

    • There are a number of new “getter” functions for accessing the index and time zone of tbl_time objects. These are useful for package development.

    • filter_time(), as_period() and other “getter” functions now use .tbl_time as a consistent first argument rather than x. collapse_index() and partition_index() use index as their first arguments.

    • Exported parse_period() for general use in other related packages.

      • @@ -205,12 +232,12 @@

      • All dplyr functions should now retain the tbl_time class and relevant attributes.

      • Ensure that tidyr::spread() passes the fill argument through.

        • -

      • Default time zone is now UTC rather than Sys.timezone() to handle a daylight savings issue.

        • +

      • Default time zone is now UTC rather than Sys.timezone() to handle a daylight savings issue.

    • -
    +

    tibbletime 0.0.2

      @@ -242,7 +269,7 @@

    • Bug Fixes

        -

      • Fixed an issue with [ in combination with tibble::add_column(). Use tibble (>= 1.3.4.9001) for correct behavior.

        • +

      • Fixed an issue with [ in combination with tibble::add_column(). Use tibble (>= 1.3.4.9001) for correct behavior.

      • Fixed a bug where using tidyr::nest() would cause the nested tibbles to lose their time attributes.

      • Fix a bug where filter_time(data, ~yyyy-mm-dd) would be parsed as yyyy-mm-dd 00:00:00 ~ yyyy-mm-dd 00:00:00 instead of yyyy-mm-dd 00:00:00 ~ yyyy-mm-dd 23:59:59.

      • Fix a bug with as.Date / as.POSIXct operator collision in filter_time().

        • @@ -250,12 +277,13 @@

    -
    +

    tibbletime 0.0.1

    • Initial release of tibbletime, a package for time aware tibbles.
    +
    @@ -263,24 +291,21 @@

    +

    Developed by Davis Vaughan, Matt Dancho.

    -

    Site built with pkgdown.

    +

    Site built with pkgdown 1.4.0.

    @@ -288,6 +313,8 @@

    Contents

    + + diff --git a/docs/pkgdown.css b/docs/pkgdown.css index 8c2e69e..9145958 100644 --- a/docs/pkgdown.css +++ b/docs/pkgdown.css @@ -21,8 +21,6 @@ body > .container { display: flex; height: 100%; flex-direction: column; - - padding-top: 60px; } body > .container .row { @@ -58,9 +56,14 @@ img { max-width: 100%; } +/* Fix bug in bootstrap (only seen in firefox) */ +summary { + display: list-item; +} + /* Typographic tweaking ---------------------------------*/ -.contents h1.page-header { +.contents .page-header { margin-top: calc(-60px + 1em); } @@ -97,21 +100,13 @@ a.anchor { margin-top: -40px; } -/* Static header placement on mobile devices */ -@media (max-width: 767px) { - .navbar-fixed-top { - position: absolute; - } - .navbar { - padding: 0; - } -} - - /* Sidebar --------------------------*/ #sidebar { margin-top: 30px; + position: -webkit-sticky; + position: sticky; + top: 70px; } #sidebar h2 { font-size: 1.5em; @@ -128,6 +123,9 @@ a.anchor { .orcid { height: 16px; + /* margins are required by official ORCID trademark and display guidelines */ + margin-left:4px; + margin-right:4px; vertical-align: middle; } @@ -217,6 +215,19 @@ a.sourceLine:hover { visibility: visible; } +/* headroom.js ------------------------ */ + +.headroom { + will-change: transform; + transition: transform 200ms linear; +} +.headroom--pinned { + transform: translateY(0%); +} +.headroom--unpinned { + transform: translateY(-100%); +} + /* mark.js ----------------------------*/ mark { @@ -229,3 +240,17 @@ mark { .html-widget { margin-bottom: 10px; } + +/* fontawesome ------------------------ */ + +.fab { + font-family: "Font Awesome 5 Brands" !important; +} + +/* don't display links in code chunks when printing */ +/* source: https://stackoverflow.com/a/10781533 */ +@media print { + code a:link:after, code a:visited:after { + content: ""; + } +} diff --git a/docs/pkgdown.js b/docs/pkgdown.js index 706ad58..087a762 100644 --- a/docs/pkgdown.js +++ b/docs/pkgdown.js @@ -2,14 +2,12 @@ (function($) { $(function() { - $("#sidebar") - .stick_in_parent({offset_top: 40}) - .on('sticky_kit:bottom', function(e) { - $(this).parent().css('position', 'static'); - }) - .on('sticky_kit:unbottom', function(e) { - $(this).parent().css('position', 'relative'); - }); + $('.navbar-fixed-top').headroom(); + + $('body').css('padding-top', $('.navbar').height() + 10); + $(window).resize(function(){ + $('body').css('padding-top', $('.navbar').height() + 10); + }); $('body').scrollspy({ target: '#sidebar', @@ -25,6 +23,10 @@ for (var i = 0; i < links.length; i++) { if (links[i].getAttribute("href") === "#") continue; + // Ignore external links + if (links[i].host !== location.host) + continue; + var nav_path = paths(links[i].pathname); var length = prefix_length(nav_path, cur_path); @@ -52,13 +54,14 @@ return(pieces); } + // Returns -1 if not found function prefix_length(needle, haystack) { if (needle.length > haystack.length) - return(0); + return(-1); // Special case for length-0 haystack, since for loop won't run if (haystack.length === 0) { - return(needle.length === 0 ? 1 : 0); + return(needle.length === 0 ? 0 : -1); } for (var i = 0; i < haystack.length; i++) { diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index 596c39c..74c9e68 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -1,6 +1,6 @@ pandoc: 2.3.1 -pkgdown: 1.1.0.9000 -pkgdown_sha: 33c059119873eb94656ec119f5ba62e86b3e7977 +pkgdown: 1.4.0 +pkgdown_sha: ~ articles: TT-01-time-based-filtering: TT-01-time-based-filtering.html TT-02-changing-time-periods: TT-02-changing-time-periods.html diff --git a/docs/reference/FANG.html b/docs/reference/FANG.html index 3b93ee4..4f006f4 100644 --- a/docs/reference/FANG.html +++ b/docs/reference/FANG.html @@ -8,21 +8,25 @@ Stock prices for Facebook, Amazon, Netflix and Google from 2013-2016 — FANG • tibbletime + - + + - + - + + - + - - + + + @@ -30,16 +34,18 @@ - + + - + + +
    @@ -136,14 +143,13 @@

    Stock prices for Facebook, Amazon, Netflix and Google from 2013-2016

    -

    A dataset containing the date, open, high, low, close, volume, and adjusted stock prices for Facebook, Amazon, Netflix and Google from 2013-2016.

    - 
    FANG
    - + +

    Format

    A tibble with 4,032 rows and 8 variables:

    @@ -155,33 +161,31 @@

    Formatclose

    stock price at the close of trading, in USD

    volume

    number of shares traded

    adjusted

    stock price at the close of trading adjusted for stock splits, in USD

    +

    -

    Source

    http://www.investopedia.com/terms/f/fang-stocks-fb-amzn.asp

    -
    + @@ -189,6 +193,8 @@

    Contents

    + + diff --git a/docs/reference/FB.html b/docs/reference/FB.html index 4732ab4..f5531e3 100644 --- a/docs/reference/FB.html +++ b/docs/reference/FB.html @@ -8,21 +8,25 @@ Stock prices for Facebook from 2013-2016 — FB • tibbletime + - + + - + - + + - + - - + + + @@ -30,16 +34,18 @@ - + + - + + +
    @@ -136,14 +143,13 @@

    Stock prices for Facebook from 2013-2016

    -

    A dataset containing the date, open, high, low, close, volume, and adjusted stock prices for Facebook from 2013-2016.

    - 
    FB
    - + +

    Format

    A tibble with 1,008 rows and 8 variables:

    @@ -155,33 +161,31 @@

    Formatclose

    stock price at the close of trading, in USD

    volume

    number of shares traded

    adjusted

    stock price at the close of trading adjusted for stock splits, in USD

    +

    -

    Source

    http://www.investopedia.com/terms/f/fang-stocks-fb-amzn.asp

    - + @@ -189,6 +193,8 @@

    Contents

    + + diff --git a/docs/reference/as_period.html b/docs/reference/as_period.html index 8904c70..48fb149 100644 --- a/docs/reference/as_period.html +++ b/docs/reference/as_period.html @@ -8,21 +8,25 @@ Change <code>tbl_time</code> periodicity — as_period • tibbletime + - + + - + - + + - + - - + + + @@ -30,8 +34,8 @@ - + + +
    @@ -138,17 +145,15 @@

    Change tbl_time periodicity

    -

    Convert a tbl_time object from daily to monthly, from minute data to hourly, and more. This allows the user to easily aggregate data to a less granular level by taking the value from either the beginning or end of the period.

    - 
    as_period(.tbl_time, period = "yearly", start_date = NULL,
   side = "start", include_endpoints = FALSE, ...)
    - +

    Arguments

    @@ -194,7 +199,7 @@

    Arg

    Not currently used.
    - +

    Details

    This function respects dplyr::group_by() groups.

    @@ -203,88 +208,87 @@

    Details

    include_endpoints can be useful when calculating a change over time. In addition to changing to monthly dates, you often need the first data point as a baseline for the first calculation.

    -

    Examples

    
 # Basic usage ---------------------------------------------------------------
 
 # FB stock prices
-data(FB)
+data(FB)
 FB <- as_tbl_time(FB, date)
 
 # Aggregate FB to yearly data
 as_period(FB, "yearly")
    #> # A time tibble: 4 x 8
-#> # Index: date
+#> # Index: date
 #>   symbol date        open  high   low close   volume adjusted
-#>   <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
-#> 1 FB     2013-01-02  27.4  28.2  27.4  28   69846400     28  
-#> 2 FB     2014-01-02  54.8  55.2  54.2  54.7 43195500     54.7
-#> 3 FB     2015-01-02  78.6  78.9  77.7  78.4 18177500     78.4
-#> 4 FB     2016-01-04 102.  102.   99.8 102.  37912400    102. 
    
+#>   <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
+#> 1 FB     2013-01-02  27.4  28.2  27.4  28   69846400     28  
+#> 2 FB     2014-01-02  54.8  55.2  54.2  54.7 43195500     54.7
+#> 3 FB     2015-01-02  78.6  78.9  77.7  78.4 18177500     78.4
+#> 4 FB     2016-01-04 102.  102.   99.8 102.  37912400    102. 
    
 # Aggregate FB to every 2 years
 as_period(FB, "2 years")
    #> # A time tibble: 3 x 8
-#> # Index: date
+#> # Index: date
 #>   symbol date        open  high   low close   volume adjusted
-#>   <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
-#> 1 FB     2013-01-02  27.4  28.2  27.4  28   69846400     28  
-#> 2 FB     2014-01-02  54.8  55.2  54.2  54.7 43195500     54.7
-#> 3 FB     2016-01-04 102.  102.   99.8 102.  37912400    102. 
    
+#>   <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
+#> 1 FB     2013-01-02  27.4  28.2  27.4  28   69846400     28  
+#> 2 FB     2014-01-02  54.8  55.2  54.2  54.7 43195500     54.7
+#> 3 FB     2016-01-04 102.  102.   99.8 102.  37912400    102. 
    
 # Aggregate FB to yearly data, but use the last data point available
 # in that period
 as_period(FB, "yearly", side = "end")
    #> # A time tibble: 4 x 8
-#> # Index: date
+#> # Index: date
 #>   symbol date        open  high   low close   volume adjusted
-#>   <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
-#> 1 FB     2013-12-31  54.1  54.9  53.9  54.7 43076200     54.7
-#> 2 FB     2014-12-31  79.5  79.8  77.9  78.0 19935400     78.0
-#> 3 FB     2015-12-31 106   106.  105.  105.  18298700    105. 
-#> 4 FB     2016-12-30 117.  117.  115.  115.  18600100    115. 
    
+#>   <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
+#> 1 FB     2013-12-31  54.1  54.9  53.9  54.7 43076200     54.7
+#> 2 FB     2014-12-31  79.5  79.8  77.9  78.0 19935400     78.0
+#> 3 FB     2015-12-31 106   106.  105.  105.  18298700    105. 
+#> 4 FB     2016-12-30 117.  117.  115.  115.  18600100    115. 
    
 # Aggregate FB to yearly data, end of period, and include the first
 # endpoint
 as_period(FB, "yearly", side = "end", include_endpoints = TRUE)
    #> # A time tibble: 5 x 8
-#> # Index: date
+#> # Index: date
 #>   symbol date        open  high   low close   volume adjusted
-#>   <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
-#> 1 FB     2013-01-02  27.4  28.2  27.4  28   69846400     28  
-#> 2 FB     2013-12-31  54.1  54.9  53.9  54.7 43076200     54.7
-#> 3 FB     2014-12-31  79.5  79.8  77.9  78.0 19935400     78.0
-#> 4 FB     2015-12-31 106   106.  105.  105.  18298700    105. 
-#> 5 FB     2016-12-30 117.  117.  115.  115.  18600100    115. 
    
+#>   <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
+#> 1 FB     2013-01-02  27.4  28.2  27.4  28   69846400     28  
+#> 2 FB     2013-12-31  54.1  54.9  53.9  54.7 43076200     54.7
+#> 3 FB     2014-12-31  79.5  79.8  77.9  78.0 19935400     78.0
+#> 4 FB     2015-12-31 106   106.  105.  105.  18298700    105. 
+#> 5 FB     2016-12-30 117.  117.  115.  115.  18600100    115. 
    
 # Aggregate to weekly. Notice that it only uses the earliest day available
 # in the data set at that periodicity. It will not set the date of the first
 # row to 2013-01-01 because that date did not exist in the original data set.
 as_period(FB, "weekly")
    #> # A time tibble: 209 x 8
-#> # Index: date
+#> # Index: date
 #>    symbol date        open  high   low close   volume adjusted
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
-#>  1 FB     2013-01-02  27.4  28.2  27.4  28   69846400     28  
-#>  2 FB     2013-01-07  28.7  29.8  28.6  29.4 83781800     29.4
-#>  3 FB     2013-01-14  32.1  32.2  30.6  31.0 98892800     31.0
-#>  4 FB     2013-01-22  29.8  30.9  29.7  30.7 55243300     30.7
-#>  5 FB     2013-01-28  31.9  32.5  31.8  32.5 59682500     32.5
-#>  6 FB     2013-02-04  29.1  29.2  28.0  28.1 92362200     28.1
-#>  7 FB     2013-02-11  28.6  28.7  28.0  28.3 37361800     28.3
-#>  8 FB     2013-02-19  28.2  29.1  28.1  28.9 49396400     28.9
-#>  9 FB     2013-02-25  27.2  27.6  27.2  27.3 34652000     27.3
-#> 10 FB     2013-03-04  27.8  28.1  27.4  27.7 32400700     27.7
-#> # … with 199 more rows
    
+#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
+#>  1 FB     2013-01-02  27.4  28.2  27.4  28   69846400     28  
+#>  2 FB     2013-01-07  28.7  29.8  28.6  29.4 83781800     29.4
+#>  3 FB     2013-01-14  32.1  32.2  30.6  31.0 98892800     31.0
+#>  4 FB     2013-01-22  29.8  30.9  29.7  30.7 55243300     30.7
+#>  5 FB     2013-01-28  31.9  32.5  31.8  32.5 59682500     32.5
+#>  6 FB     2013-02-04  29.1  29.2  28.0  28.1 92362200     28.1
+#>  7 FB     2013-02-11  28.6  28.7  28.0  28.3 37361800     28.3
+#>  8 FB     2013-02-19  28.2  29.1  28.1  28.9 49396400     28.9
+#>  9 FB     2013-02-25  27.2  27.6  27.2  27.3 34652000     27.3
+#> 10 FB     2013-03-04  27.8  28.1  27.4  27.7 32400700     27.7
+#> # … with 199 more rows
    
 # Aggregate to every other week
 as_period(FB, "2 weeks")
    #> Warning: Multi-unit not supported for weeks. Ignoring.
    #> Warning: Multi-unit not supported for weeks. Ignoring.
    #> # A time tibble: 105 x 8
-#> # Index: date
+#> # Index: date
 #>    symbol date        open  high   low close   volume adjusted
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
-#>  1 FB     2013-01-02  27.4  28.2  27.4  28   69846400     28  
-#>  2 FB     2013-01-14  32.1  32.2  30.6  31.0 98892800     31.0
-#>  3 FB     2013-01-28  31.9  32.5  31.8  32.5 59682500     32.5
-#>  4 FB     2013-02-11  28.6  28.7  28.0  28.3 37361800     28.3
-#>  5 FB     2013-02-25  27.2  27.6  27.2  27.3 34652000     27.3
-#>  6 FB     2013-03-11  28.0  28.6  27.8  28.1 35642100     28.1
-#>  7 FB     2013-03-25  25.8  25.8  25.1  25.1 39199000     25.1
-#>  8 FB     2013-04-08  27.2  27.2  26.6  26.8 27256000     26.8
-#>  9 FB     2013-04-22  25.8  26.4  25.7  26.0 25687600     26.0
-#> 10 FB     2013-05-06  28.3  28.5  27.5  27.6 43939400     27.6
-#> # … with 95 more rows
    
+#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
+#>  1 FB     2013-01-02  27.4  28.2  27.4  28   69846400     28  
+#>  2 FB     2013-01-14  32.1  32.2  30.6  31.0 98892800     31.0
+#>  3 FB     2013-01-28  31.9  32.5  31.8  32.5 59682500     32.5
+#>  4 FB     2013-02-11  28.6  28.7  28.0  28.3 37361800     28.3
+#>  5 FB     2013-02-25  27.2  27.6  27.2  27.3 34652000     27.3
+#>  6 FB     2013-03-11  28.0  28.6  27.8  28.1 35642100     28.1
+#>  7 FB     2013-03-25  25.8  25.8  25.1  25.1 39199000     25.1
+#>  8 FB     2013-04-08  27.2  27.2  26.6  26.8 27256000     26.8
+#>  9 FB     2013-04-22  25.8  26.4  25.7  26.0 25687600     26.0
+#> 10 FB     2013-05-06  28.3  28.5  27.5  27.6 43939400     27.6
+#> # … with 95 more rows
    
 # FB is daily data, aggregate to minute?
 # Not allowed for Date class indices, an error is thrown
 # as_period(FB, "minute")
@@ -292,98 +296,98 @@ 
    Examp
 # Grouped usage -------------------------------------------------------------
 
 # FANG contains Facebook, Amazon, Netflix and Google stock prices
-data(FANG)
+data(FANG)
 FANG <- as_tbl_time(FANG, date)
 
 FANG <- dplyr::group_by(FANG, symbol)
 
 # Respects groups
 as_period(FANG, "yearly")
    #> # A time tibble: 16 x 8
-#> # Index:  date
-#> # Groups: symbol [4]
+#> # Index:  date
+#> # Groups: symbol [4]
 #>    symbol date         open   high    low  close   volume adjusted
-#>    <chr>  <date>      <dbl>  <dbl>  <dbl>  <dbl>    <dbl>    <dbl>
-#>  1 FB     2013-01-02   27.4   28.2   27.4   28   69846400     28  
-#>  2 FB     2014-01-02   54.8   55.2   54.2   54.7 43195500     54.7
-#>  3 FB     2015-01-02   78.6   78.9   77.7   78.4 18177500     78.4
-#>  4 FB     2016-01-04  102.   102.    99.8  102.  37912400    102. 
-#>  5 AMZN   2013-01-02  256.   258.   253.   257.   3271000    257. 
-#>  6 AMZN   2014-01-02  399.   399.   394.   398.   2137800    398. 
-#>  7 AMZN   2015-01-02  313.   315.   307.   309.   2783200    309. 
-#>  8 AMZN   2016-01-04  656.   658.   628.   637.   9314500    637. 
-#>  9 NFLX   2013-01-02   95.2   95.8   90.7   92.0 19431300     13.1
-#> 10 NFLX   2014-01-02  367.   368.   361.   363.  12325600     51.8
-#> 11 NFLX   2015-01-02  344.   352.   341.   349.  13475000     49.8
-#> 12 NFLX   2016-01-04  109    110    105.   110.  20794800    110. 
-#> 13 GOOG   2013-01-02  719.   727.   717.   723.   5101500    361. 
-#> 14 GOOG   2014-01-02 1115.  1118.  1108.  1113.   3656400    556. 
-#> 15 GOOG   2015-01-02  529.   531.   524.   525.   1447500    525. 
-#> 16 GOOG   2016-01-04  743    744.   731.   742.   3272800    742. 
    
+#>    <chr>  <date>      <dbl>  <dbl>  <dbl>  <dbl>    <dbl>    <dbl>
+#>  1 FB     2013-01-02   27.4   28.2   27.4   28   69846400     28  
+#>  2 FB     2014-01-02   54.8   55.2   54.2   54.7 43195500     54.7
+#>  3 FB     2015-01-02   78.6   78.9   77.7   78.4 18177500     78.4
+#>  4 FB     2016-01-04  102.   102.    99.8  102.  37912400    102. 
+#>  5 AMZN   2013-01-02  256.   258.   253.   257.   3271000    257. 
+#>  6 AMZN   2014-01-02  399.   399.   394.   398.   2137800    398. 
+#>  7 AMZN   2015-01-02  313.   315.   307.   309.   2783200    309. 
+#>  8 AMZN   2016-01-04  656.   658.   628.   637.   9314500    637. 
+#>  9 NFLX   2013-01-02   95.2   95.8   90.7   92.0 19431300     13.1
+#> 10 NFLX   2014-01-02  367.   368.   361.   363.  12325600     51.8
+#> 11 NFLX   2015-01-02  344.   352.   341.   349.  13475000     49.8
+#> 12 NFLX   2016-01-04  109    110    105.   110.  20794800    110. 
+#> 13 GOOG   2013-01-02  719.   727.   717.   723.   5101500    361. 
+#> 14 GOOG   2014-01-02 1115.  1118.  1108.  1113.   3656400    556. 
+#> 15 GOOG   2015-01-02  529.   531.   524.   525.   1447500    525. 
+#> 16 GOOG   2016-01-04  743    744.   731.   742.   3272800    742. 
    
 # Every 6 months, respecting groups
 as_period(FANG, "6 months")
    #> # A time tibble: 32 x 8
-#> # Index:  date
-#> # Groups: symbol [4]
+#> # Index:  date
+#> # Groups: symbol [4]
 #>    symbol date        open  high   low close   volume adjusted
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
-#>  1 FB     2013-01-02  27.4  28.2  27.4  28   69846400     28  
-#>  2 FB     2013-07-01  25.0  25.1  24.6  24.8 20582200     24.8
-#>  3 FB     2014-01-02  54.8  55.2  54.2  54.7 43195500     54.7
-#>  4 FB     2014-07-01  67.6  68.4  67.4  68.1 33243000     68.1
-#>  5 FB     2015-01-02  78.6  78.9  77.7  78.4 18177500     78.4
-#>  6 FB     2015-07-01  86.8  87.9  86.5  86.9 25260000     86.9
-#>  7 FB     2016-01-04 102.  102.   99.8 102.  37912400    102. 
-#>  8 FB     2016-07-01 114.  115.  114.  114.  14980000    114. 
-#>  9 AMZN   2013-01-02 256.  258.  253.  257.   3271000    257. 
-#> 10 AMZN   2013-07-01 279   283.  277.  282.   2888200    282. 
-#> # … with 22 more rows
    
+#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
+#>  1 FB     2013-01-02  27.4  28.2  27.4  28   69846400     28  
+#>  2 FB     2013-07-01  25.0  25.1  24.6  24.8 20582200     24.8
+#>  3 FB     2014-01-02  54.8  55.2  54.2  54.7 43195500     54.7
+#>  4 FB     2014-07-01  67.6  68.4  67.4  68.1 33243000     68.1
+#>  5 FB     2015-01-02  78.6  78.9  77.7  78.4 18177500     78.4
+#>  6 FB     2015-07-01  86.8  87.9  86.5  86.9 25260000     86.9
+#>  7 FB     2016-01-04 102.  102.   99.8 102.  37912400    102. 
+#>  8 FB     2016-07-01 114.  115.  114.  114.  14980000    114. 
+#>  9 AMZN   2013-01-02 256.  258.  253.  257.   3271000    257. 
+#> 10 AMZN   2013-07-01 279   283.  277.  282.   2888200    282. 
+#> # … with 22 more rows
    
 # Using start_date ----------------------------------------------------------
 
 
 #### One method using start_date
 
 # FB stock prices
-data(FB)
+data(FB)
 FB <- as_tbl_time(FB, date)
 
 # The Facebook series starts at 2013-01-02 so the 'every 2 day' counter
 # starts at that date as well. Groups become (2013-01-02, 2013-01-03),
 # (2013-01-04, 2013-01-05) and so on.
 as_period(FB, "2 day")
    #> # A time tibble: 619 x 8
-#> # Index: date
+#> # Index: date
 #>    symbol date        open  high   low close    volume adjusted
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
-#>  1 FB     2013-01-02  27.4  28.2  27.4  28    69846400     28  
-#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8  63140600     27.8
-#>  3 FB     2013-01-07  28.7  29.8  28.6  29.4  83781800     29.4
-#>  4 FB     2013-01-09  29.7  30.6  29.5  30.6 104787700     30.6
-#>  5 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7
-#>  6 FB     2013-01-14  32.1  32.2  30.6  31.0  98892800     31.0
-#>  7 FB     2013-01-15  30.6  31.7  29.9  30.1 173242600     30.1
-#>  8 FB     2013-01-17  30.1  30.4  30.0  30.1  40256700     30.1
-#>  9 FB     2013-01-22  29.8  30.9  29.7  30.7  55243300     30.7
-#> 10 FB     2013-01-23  31.1  31.5  30.8  30.8  48899800     30.8
-#> # … with 609 more rows
    
+#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
+#>  1 FB     2013-01-02  27.4  28.2  27.4  28    69846400     28  
+#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8  63140600     27.8
+#>  3 FB     2013-01-07  28.7  29.8  28.6  29.4  83781800     29.4
+#>  4 FB     2013-01-09  29.7  30.6  29.5  30.6 104787700     30.6
+#>  5 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7
+#>  6 FB     2013-01-14  32.1  32.2  30.6  31.0  98892800     31.0
+#>  7 FB     2013-01-15  30.6  31.7  29.9  30.1 173242600     30.1
+#>  8 FB     2013-01-17  30.1  30.4  30.0  30.1  40256700     30.1
+#>  9 FB     2013-01-22  29.8  30.9  29.7  30.7  55243300     30.7
+#> 10 FB     2013-01-23  31.1  31.5  30.8  30.8  48899800     30.8
+#> # … with 609 more rows
    
 # Specifying the `start_date = "2013-01-01"` might be preferable.
 # Groups become (2013-01-01, 2013-01-02), (2013-01-03, 2013-01-04) and so on.
 as_period(FB, "2 day", start_date = "2013-01-01")
    #> # A time tibble: 619 x 8
-#> # Index: date
+#> # Index: date
 #>    symbol date        open  high   low close    volume adjusted
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
-#>  1 FB     2013-01-02  27.4  28.2  27.4  28    69846400     28  
-#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8  63140600     27.8
-#>  3 FB     2013-01-07  28.7  29.8  28.6  29.4  83781800     29.4
-#>  4 FB     2013-01-09  29.7  30.6  29.5  30.6 104787700     30.6
-#>  5 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7
-#>  6 FB     2013-01-14  32.1  32.2  30.6  31.0  98892800     31.0
-#>  7 FB     2013-01-15  30.6  31.7  29.9  30.1 173242600     30.1
-#>  8 FB     2013-01-17  30.1  30.4  30.0  30.1  40256700     30.1
-#>  9 FB     2013-01-22  29.8  30.9  29.7  30.7  55243300     30.7
-#> 10 FB     2013-01-23  31.1  31.5  30.8  30.8  48899800     30.8
-#> # … with 609 more rows
    
+#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
+#>  1 FB     2013-01-02  27.4  28.2  27.4  28    69846400     28  
+#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8  63140600     27.8
+#>  3 FB     2013-01-07  28.7  29.8  28.6  29.4  83781800     29.4
+#>  4 FB     2013-01-09  29.7  30.6  29.5  30.6 104787700     30.6
+#>  5 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7
+#>  6 FB     2013-01-14  32.1  32.2  30.6  31.0  98892800     31.0
+#>  7 FB     2013-01-15  30.6  31.7  29.9  30.1 173242600     30.1
+#>  8 FB     2013-01-17  30.1  30.4  30.0  30.1  40256700     30.1
+#>  9 FB     2013-01-22  29.8  30.9  29.7  30.7  55243300     30.7
+#> 10 FB     2013-01-23  31.1  31.5  30.8  30.8  48899800     30.8
+#> # … with 609 more rows
    
 #### Equivalent method using an index vector
 
 # FB stock prices
-data(FB)
+data(FB)
 FB <- as_tbl_time(FB, date)
 
 custom_period <- create_series(
@@ -395,23 +399,23 @@ 
    Examp
 FB %>%
   as_tbl_time(date) %>%
   as_period(period = custom_period)
    #> # A time tibble: 619 x 8
-#> # Index: date
+#> # Index: date
 #>    symbol date        open  high   low close    volume adjusted
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
-#>  1 FB     2013-01-02  27.4  28.2  27.4  28    69846400     28  
-#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8  63140600     27.8
-#>  3 FB     2013-01-07  28.7  29.8  28.6  29.4  83781800     29.4
-#>  4 FB     2013-01-09  29.7  30.6  29.5  30.6 104787700     30.6
-#>  5 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7
-#>  6 FB     2013-01-14  32.1  32.2  30.6  31.0  98892800     31.0
-#>  7 FB     2013-01-15  30.6  31.7  29.9  30.1 173242600     30.1
-#>  8 FB     2013-01-17  30.1  30.4  30.0  30.1  40256700     30.1
-#>  9 FB     2013-01-22  29.8  30.9  29.7  30.7  55243300     30.7
-#> 10 FB     2013-01-23  31.1  31.5  30.8  30.8  48899800     30.8
-#> # … with 609 more rows
    
+#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
+#>  1 FB     2013-01-02  27.4  28.2  27.4  28    69846400     28  
+#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8  63140600     27.8
+#>  3 FB     2013-01-07  28.7  29.8  28.6  29.4  83781800     29.4
+#>  4 FB     2013-01-09  29.7  30.6  29.5  30.6 104787700     30.6
+#>  5 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7
+#>  6 FB     2013-01-14  32.1  32.2  30.6  31.0  98892800     31.0
+#>  7 FB     2013-01-15  30.6  31.7  29.9  30.1 173242600     30.1
+#>  8 FB     2013-01-17  30.1  30.4  30.0  30.1  40256700     30.1
+#>  9 FB     2013-01-22  29.8  30.9  29.7  30.7  55243300     30.7
+#> 10 FB     2013-01-23  31.1  31.5  30.8  30.8  48899800     30.8
+#> # … with 609 more rows
    
 # Manually calculating returns at different periods -------------------------
 
-data(FB)
+data(FB)
 
 # Annual Returns
 # Convert to end of year periodicity, but include the endpoints to use as
@@ -420,36 +424,35 @@ 
    Examp
   as_tbl_time(date) %>%
   as_period("1 y", side = "end", include_endpoints = TRUE) %>%
   dplyr::mutate(yearly_return = adjusted / dplyr::lag(adjusted) - 1)
    #> # A time tibble: 5 x 9
-#> # Index: date
+#> # Index: date
 #>   symbol date        open  high   low close   volume adjusted yearly_return
-#>   <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>         <dbl>
-#> 1 FB     2013-01-02  27.4  28.2  27.4  28   69846400     28         NA     
-#> 2 FB     2013-12-31  54.1  54.9  53.9  54.7 43076200     54.7        0.952 
-#> 3 FB     2014-12-31  79.5  79.8  77.9  78.0 19935400     78.0        0.428 
-#> 4 FB     2015-12-31 106   106.  105.  105.  18298700    105.         0.341 
-#> 5 FB     2016-12-30 117.  117.  115.  115.  18600100    115.         0.0993
    
-
    +#> <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 FB 2013-01-02 27.4 28.2 27.4 28 69846400 28 NA +#> 2 FB 2013-12-31 54.1 54.9 53.9 54.7 43076200 54.7 0.952 +#> 3 FB 2014-12-31 79.5 79.8 77.9 78.0 19935400 78.0 0.428 +#> 4 FB 2015-12-31 106 106. 105. 105. 18298700 105. 0.341 +#> 5 FB 2016-12-30 117. 117. 115. 115. 18600100 115. 0.0993
    +
     + @@ -457,6 +460,8 @@

    Contents

    + + diff --git a/docs/reference/ceiling_index.html b/docs/reference/ceiling_index.html index 7608d15..2a6cced 100644 --- a/docs/reference/ceiling_index.html +++ b/docs/reference/ceiling_index.html @@ -8,21 +8,25 @@ A simple wrapper of <code><a href='http://lubridate.tidyverse.org/reference/round_date.html'>lubridate::ceiling_date()</a></code> — ceiling_index • tibbletime + - + + - + - + + - + - - + + + @@ -30,16 +34,18 @@ - + + - + + +
    @@ -136,14 +143,12 @@

    A simple wrapper of lubridate::ceiling_date() that works for hms, yearmon, and yearqtr classes as well.

    - 

    ceiling_index(x, unit = "seconds")
    - +

    Arguments

    @@ -161,69 +166,67 @@

    Arg supported.

    - +

    See also

    lubridate::ceiling_date()

    -

    Examples

    
-data(FB)
-dplyr::mutate(FB, date2 = ceiling_index(date, "year"))
    #> # A tibble: 1,008 x 9
+data(FB)
+dplyr::mutate(FB, date2 = ceiling_index(date, "year"))
    #> # A tibble: 1,008 x 9
 #>    symbol date        open  high   low close    volume adjusted date2     
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl> <date>    
-#>  1 FB     2013-01-02  27.4  28.2  27.4  28    69846400     28   2014-01-01
-#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8  63140600     27.8 2014-01-01
-#>  3 FB     2013-01-04  28.0  28.9  27.8  28.8  72715400     28.8 2014-01-01
-#>  4 FB     2013-01-07  28.7  29.8  28.6  29.4  83781800     29.4 2014-01-01
-#>  5 FB     2013-01-08  29.5  29.6  28.9  29.1  45871300     29.1 2014-01-01
-#>  6 FB     2013-01-09  29.7  30.6  29.5  30.6 104787700     30.6 2014-01-01
-#>  7 FB     2013-01-10  30.6  31.5  30.3  31.3  95316400     31.3 2014-01-01
-#>  8 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7 2014-01-01
-#>  9 FB     2013-01-14  32.1  32.2  30.6  31.0  98892800     31.0 2014-01-01
-#> 10 FB     2013-01-15  30.6  31.7  29.9  30.1 173242600     30.1 2014-01-01
-#> # … with 998 more rows
    
+#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl> <date>    
+#>  1 FB     2013-01-02  27.4  28.2  27.4  28    69846400     28   2014-01-01
+#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8  63140600     27.8 2014-01-01
+#>  3 FB     2013-01-04  28.0  28.9  27.8  28.8  72715400     28.8 2014-01-01
+#>  4 FB     2013-01-07  28.7  29.8  28.6  29.4  83781800     29.4 2014-01-01
+#>  5 FB     2013-01-08  29.5  29.6  28.9  29.1  45871300     29.1 2014-01-01
+#>  6 FB     2013-01-09  29.7  30.6  29.5  30.6 104787700     30.6 2014-01-01
+#>  7 FB     2013-01-10  30.6  31.5  30.3  31.3  95316400     31.3 2014-01-01
+#>  8 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7 2014-01-01
+#>  9 FB     2013-01-14  32.1  32.2  30.6  31.0  98892800     31.0 2014-01-01
+#> 10 FB     2013-01-15  30.6  31.7  29.9  30.1 173242600     30.1 2014-01-01
+#> # … with 998 more rows
    
 time_test <- create_series('00:00:00'~'12:00:00',
                            '1 minute', class = "hms")
 
 dplyr::mutate(time_test, date2 = ceiling_index(date, "hour"))
    #> # A time tibble: 721 x 2
-#> # Index: date
+#> # Index: date
 #>    date   date2 
-#>    <time> <time>
-#>  1 00'00" 00:00 
-#>  2 01'00" 01:00 
-#>  3 02'00" 01:00 
-#>  4 03'00" 01:00 
-#>  5 04'00" 01:00 
-#>  6 05'00" 01:00 
-#>  7 06'00" 01:00 
-#>  8 07'00" 01:00 
-#>  9 08'00" 01:00 
-#> 10 09'00" 01:00 
-#> # … with 711 more rows
    
-
    +#> <time> <time> +#> 1 00'00" 00:00 +#> 2 01'00" 01:00 +#> 3 02'00" 01:00 +#> 4 03'00" 01:00 +#> 5 04'00" 01:00 +#> 6 05'00" 01:00 +#> 7 06'00" 01:00 +#> 8 07'00" 01:00 +#> 9 08'00" 01:00 +#> 10 09'00" 01:00 +#> # … with 711 more rows
    +
     + @@ -231,6 +234,8 @@

    Contents

    + + diff --git a/docs/reference/collapse_by.html b/docs/reference/collapse_by.html index 78d90fb..6e1f0c8 100644 --- a/docs/reference/collapse_by.html +++ b/docs/reference/collapse_by.html @@ -8,21 +8,25 @@ Collapse a tbl_time object by its index — collapse_by • tibbletime + - + + - + - + + - + - - + + + @@ -30,8 +34,8 @@ - + @@ -39,8 +43,10 @@ + - + + +
    @@ -137,16 +144,14 @@

    Collapse a tbl_time object by its index

    -

    Collapse the index of a tbl_time object by time period. The index column is altered so that all dates that fall in a specified interval share a common date.

    - 
    collapse_by(.tbl_time, period = "yearly", start_date = NULL,
   side = "end", clean = FALSE, ...)
    - +

    Arguments

    @@ -193,53 +198,52 @@

    Arg

    Not currently used.
    - +

    Details

    collapse_by() is a simplification of a call to dplyr::mutate() to collapse an index column using collapse_index().

    -

    Examples

    
 # Basic functionality -------------------------------------------------------
 
 # Facebook stock prices
-data(FB)
+data(FB)
 FB <- as_tbl_time(FB, date)
 
 # Collapse to weekly dates
 collapse_by(FB, "weekly")
    #> # A time tibble: 1,008 x 8
-#> # Index: date
+#> # Index: date
 #>    symbol date        open  high   low close    volume adjusted
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
-#>  1 FB     2013-01-04  27.4  28.2  27.4  28    69846400     28  
-#>  2 FB     2013-01-04  27.9  28.5  27.6  27.8  63140600     27.8
-#>  3 FB     2013-01-04  28.0  28.9  27.8  28.8  72715400     28.8
-#>  4 FB     2013-01-11  28.7  29.8  28.6  29.4  83781800     29.4
-#>  5 FB     2013-01-11  29.5  29.6  28.9  29.1  45871300     29.1
-#>  6 FB     2013-01-11  29.7  30.6  29.5  30.6 104787700     30.6
-#>  7 FB     2013-01-11  30.6  31.5  30.3  31.3  95316400     31.3
-#>  8 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7
-#>  9 FB     2013-01-18  32.1  32.2  30.6  31.0  98892800     31.0
-#> 10 FB     2013-01-18  30.6  31.7  29.9  30.1 173242600     30.1
-#> # … with 998 more rows
    
+#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
+#>  1 FB     2013-01-04  27.4  28.2  27.4  28    69846400     28  
+#>  2 FB     2013-01-04  27.9  28.5  27.6  27.8  63140600     27.8
+#>  3 FB     2013-01-04  28.0  28.9  27.8  28.8  72715400     28.8
+#>  4 FB     2013-01-11  28.7  29.8  28.6  29.4  83781800     29.4
+#>  5 FB     2013-01-11  29.5  29.6  28.9  29.1  45871300     29.1
+#>  6 FB     2013-01-11  29.7  30.6  29.5  30.6 104787700     30.6
+#>  7 FB     2013-01-11  30.6  31.5  30.3  31.3  95316400     31.3
+#>  8 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7
+#>  9 FB     2013-01-18  32.1  32.2  30.6  31.0  98892800     31.0
+#> 10 FB     2013-01-18  30.6  31.7  29.9  30.1 173242600     30.1
+#> # … with 998 more rows
    
 # A common workflow is to group on the collapsed date column
 # to perform a time based summary
 FB %>%
   collapse_by("yearly") %>%
   dplyr::group_by(date) %>%
   dplyr::summarise_if(is.numeric, mean)
    #> # A time tibble: 4 x 7
-#> # Index: date
+#> # Index: date
 #>   date        open  high   low close    volume adjusted
-#>   <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
-#> 1 2013-12-31  35.5  36.0  34.9  35.5 60091994.     35.5
-#> 2 2014-12-31  68.8  69.6  67.8  68.8 47530552.     68.8
-#> 3 2015-12-31  88.7  89.7  87.8  88.8 26955191.     88.8
-#> 4 2016-12-30 117.  118.  116.  117.  25453798.    117. 
    
+#>   <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
+#> 1 2013-12-31  35.5  36.0  34.9  35.5 60091994.     35.5
+#> 2 2014-12-31  68.8  69.6  67.8  68.8 47530552.     68.8
+#> 3 2015-12-31  88.7  89.7  87.8  88.8 26955191.     88.8
+#> 4 2016-12-30 117.  118.  116.  117.  25453798.    117. 
    
 # Grouped functionality -----------------------------------------------------
 
-data(FANG)
+data(FANG)
 FANG <- FANG %>%
   as_tbl_time(date) %>%
   dplyr::group_by(symbol)
@@ -250,43 +254,42 @@ 
    Examp
   collapse_by("monthly") %>%
   dplyr::group_by(date, add = TRUE) %>%
   dplyr::summarise_all(sd)
    #> # A time tibble: 192 x 8
-#> # Index:  date
-#> # Groups: symbol [?]
+#> # Index:  date
+#> # Groups: symbol [4]
 #>    symbol date        open  high   low close   volume adjusted
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
-#>  1 AMZN   2013-01-31  7.11  7.21  5.63  6.31 2851878.     6.31
-#>  2 AMZN   2013-02-28  3.21  3.38  3.26  3.82  863971.     3.82
-#>  3 AMZN   2013-03-28  7.50  7.29  7.51  7.67  929111.     7.67
-#>  4 AMZN   2013-04-30  6.32  6.22  6.15  6.69 2688623.     6.69
-#>  5 AMZN   2013-05-31  5.40  5.60  6.44  5.72  781265.     5.72
-#>  6 AMZN   2013-06-28  4.29  4.45  4.91  4.70  692542.     4.70
-#>  7 AMZN   2013-07-31 10.1   9.68  9.09  9.04 1592530.     9.04
-#>  8 AMZN   2013-08-30  7.67  7.08  6.98  7.65  443340.     7.65
-#>  9 AMZN   2013-09-30  9.67  9.37  9.37  9.18  847804.     9.18
-#> 10 AMZN   2013-10-31 20.6  21.4  20.7  21.4  2209026.    21.4 
-#> # … with 182 more rows
    
-
    +#> <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 AMZN 2013-01-31 7.11 7.21 5.63 6.31 2851878. 6.31 +#> 2 AMZN 2013-02-28 3.21 3.38 3.26 3.82 863971. 3.82 +#> 3 AMZN 2013-03-28 7.50 7.29 7.51 7.67 929111. 7.67 +#> 4 AMZN 2013-04-30 6.32 6.22 6.15 6.69 2688623. 6.69 +#> 5 AMZN 2013-05-31 5.40 5.60 6.44 5.72 781265. 5.72 +#> 6 AMZN 2013-06-28 4.29 4.45 4.91 4.70 692542. 4.70 +#> 7 AMZN 2013-07-31 10.1 9.68 9.09 9.04 1592530. 9.04 +#> 8 AMZN 2013-08-30 7.67 7.08 6.98 7.65 443340. 7.65 +#> 9 AMZN 2013-09-30 9.67 9.37 9.37 9.18 847804. 9.18 +#> 10 AMZN 2013-10-31 20.6 21.4 20.7 21.4 2209026. 21.4 +#> # … with 182 more rows
    +
     + @@ -294,6 +297,8 @@

    Contents

    + + diff --git a/docs/reference/collapse_index.html b/docs/reference/collapse_index.html index 8fb208d..8fd187c 100644 --- a/docs/reference/collapse_index.html +++ b/docs/reference/collapse_index.html @@ -9,21 +9,25 @@ Collapse an index vector so that all observations in an interval share the same date — collapse_index • tibbletime + - + + - + - + + - + - - + + + @@ -31,9 +35,9 @@ + - @@ -41,8 +45,10 @@ + - + + +
    @@ -140,16 +147,14 @@

    Collapse an index vector so that all observations in an interval share the

    -

    When collapse_index() is used, the index vector is altered so that all dates that fall in a specified interval share a common date. The most common use case for this is to then group on the collapsed index.

    - 
    collapse_index(index, period = "yearly", start_date = NULL,
   side = "end", clean = FALSE, ...)
    - +

    Arguments

    @@ -196,7 +201,7 @@

    Arg

    Not currently used.
    - +

    Details

    The collapse_by() function provides a shortcut for the most common use @@ -204,64 +209,64 @@

    Details modify the index directly. For more flexibility, like the nesting example below, use collapse_index().

    Because this is often used for end of period summaries, the default is to -use side = "end". Note that this is the opposite of as_period() where -the default is side = "start".

    +use side = "end". Note that this is the opposite of as_period() where +the default is side = "start".

    The clean argument is especially useful if you have an irregular series and want cleaner dates to report for summary values.

    -

    Examples

    
 # Basic functionality -------------------------------------------------------
 
 # Facebook stock prices
-data(FB)
+data(FB)
 FB <- as_tbl_time(FB, date)
 
 # Collapse to weekly dates
 dplyr::mutate(FB, date = collapse_index(date, "weekly"))
    #> # A time tibble: 1,008 x 8
-#> # Index: date
+#> # Index: date
 #>    symbol date        open  high   low close    volume adjusted
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
-#>  1 FB     2013-01-04  27.4  28.2  27.4  28    69846400     28  
-#>  2 FB     2013-01-04  27.9  28.5  27.6  27.8  63140600     27.8
-#>  3 FB     2013-01-04  28.0  28.9  27.8  28.8  72715400     28.8
-#>  4 FB     2013-01-11  28.7  29.8  28.6  29.4  83781800     29.4
-#>  5 FB     2013-01-11  29.5  29.6  28.9  29.1  45871300     29.1
-#>  6 FB     2013-01-11  29.7  30.6  29.5  30.6 104787700     30.6
-#>  7 FB     2013-01-11  30.6  31.5  30.3  31.3  95316400     31.3
-#>  8 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7
-#>  9 FB     2013-01-18  32.1  32.2  30.6  31.0  98892800     31.0
-#> 10 FB     2013-01-18  30.6  31.7  29.9  30.1 173242600     30.1
-#> # … with 998 more rows
    
+#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
+#>  1 FB     2013-01-04  27.4  28.2  27.4  28    69846400     28  
+#>  2 FB     2013-01-04  27.9  28.5  27.6  27.8  63140600     27.8
+#>  3 FB     2013-01-04  28.0  28.9  27.8  28.8  72715400     28.8
+#>  4 FB     2013-01-11  28.7  29.8  28.6  29.4  83781800     29.4
+#>  5 FB     2013-01-11  29.5  29.6  28.9  29.1  45871300     29.1
+#>  6 FB     2013-01-11  29.7  30.6  29.5  30.6 104787700     30.6
+#>  7 FB     2013-01-11  30.6  31.5  30.3  31.3  95316400     31.3
+#>  8 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7
+#>  9 FB     2013-01-18  32.1  32.2  30.6  31.0  98892800     31.0
+#> 10 FB     2013-01-18  30.6  31.7  29.9  30.1 173242600     30.1
+#> # … with 998 more rows
    
 # A common workflow is to group on the new date column
 # to perform a time based summary
 FB %>%
   dplyr::mutate(date = collapse_index(date, "yearly")) %>%
   dplyr::group_by(date) %>%
   dplyr::summarise_if(is.numeric, mean)
    #> # A time tibble: 4 x 7
-#> # Index: date
+#> # Index: date
 #>   date        open  high   low close    volume adjusted
-#>   <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
-#> 1 2013-12-31  35.5  36.0  34.9  35.5 60091994.     35.5
-#> 2 2014-12-31  68.8  69.6  67.8  68.8 47530552.     68.8
-#> 3 2015-12-31  88.7  89.7  87.8  88.8 26955191.     88.8
-#> 4 2016-12-30 117.  118.  116.  117.  25453798.    117. 
    
+#>   <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
+#> 1 2013-12-31  35.5  36.0  34.9  35.5 60091994.     35.5
+#> 2 2014-12-31  68.8  69.6  67.8  68.8 47530552.     68.8
+#> 3 2015-12-31  88.7  89.7  87.8  88.8 26955191.     88.8
+#> 4 2016-12-30 117.  118.  116.  117.  25453798.    117. 
    
 # You can also assign the result to a separate column and use that
 # to nest on, allowing for 'period nests' that keep the
 # original dates in the nested tibbles.
 FB %>%
   dplyr::mutate(nest_date = collapse_index(date, "2 year")) %>%
   dplyr::group_by(nest_date) %>%
-  tidyr::nest()
    #> # A tibble: 3 x 2
-#>   nest_date  data              
-#>   <date>     <list>            
-#> 1 2013-12-31 <tibble [252 × 8]>
-#> 2 2015-12-31 <tibble [504 × 8]>
-#> 3 2016-12-30 <tibble [252 × 8]>
    
+  tidyr::nest()
    #> # A tibble: 3 x 2
+#> # Groups:   nest_date [3]
+#>   nest_date            data
+#>   <date>     <list<df[,8]>>
+#> 1 2013-12-31      [252 × 8]
+#> 2 2015-12-31      [504 × 8]
+#> 3 2016-12-30      [252 × 8]
    
 # Grouped functionality -----------------------------------------------------
 
-data(FANG)
+data(FANG)
 FANG <- FANG %>%
   as_tbl_time(date) %>%
   dplyr::group_by(symbol)
@@ -272,44 +277,43 @@ 
    Examp
   dplyr::mutate(date = collapse_index(date, "monthly")) %>%
   dplyr::group_by(date, add = TRUE) %>%
   dplyr::summarise_all(sd)
    #> # A time tibble: 192 x 8
-#> # Index:  date
-#> # Groups: symbol [?]
+#> # Index:  date
+#> # Groups: symbol [4]
 #>    symbol date        open  high   low close   volume adjusted
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
-#>  1 AMZN   2013-01-31  7.11  7.21  5.63  6.31 2851878.     6.31
-#>  2 AMZN   2013-02-28  3.21  3.38  3.26  3.82  863971.     3.82
-#>  3 AMZN   2013-03-28  7.50  7.29  7.51  7.67  929111.     7.67
-#>  4 AMZN   2013-04-30  6.32  6.22  6.15  6.69 2688623.     6.69
-#>  5 AMZN   2013-05-31  5.40  5.60  6.44  5.72  781265.     5.72
-#>  6 AMZN   2013-06-28  4.29  4.45  4.91  4.70  692542.     4.70
-#>  7 AMZN   2013-07-31 10.1   9.68  9.09  9.04 1592530.     9.04
-#>  8 AMZN   2013-08-30  7.67  7.08  6.98  7.65  443340.     7.65
-#>  9 AMZN   2013-09-30  9.67  9.37  9.37  9.18  847804.     9.18
-#> 10 AMZN   2013-10-31 20.6  21.4  20.7  21.4  2209026.    21.4 
-#> # … with 182 more rows
    
-
-
    +#> <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 AMZN 2013-01-31 7.11 7.21 5.63 6.31 2851878. 6.31 +#> 2 AMZN 2013-02-28 3.21 3.38 3.26 3.82 863971. 3.82 +#> 3 AMZN 2013-03-28 7.50 7.29 7.51 7.67 929111. 7.67 +#> 4 AMZN 2013-04-30 6.32 6.22 6.15 6.69 2688623. 6.69 +#> 5 AMZN 2013-05-31 5.40 5.60 6.44 5.72 781265. 5.72 +#> 6 AMZN 2013-06-28 4.29 4.45 4.91 4.70 692542. 4.70 +#> 7 AMZN 2013-07-31 10.1 9.68 9.09 9.04 1592530. 9.04 +#> 8 AMZN 2013-08-30 7.67 7.08 6.98 7.65 443340. 7.65 +#> 9 AMZN 2013-09-30 9.67 9.37 9.37 9.18 847804. 9.18 +#> 10 AMZN 2013-10-31 20.6 21.4 20.7 21.4 2209026. 21.4 +#> # … with 182 more rows
    + +
     + @@ -317,6 +321,8 @@

    Contents

    + + diff --git a/docs/reference/create_series.html b/docs/reference/create_series.html index fc55622..3d0d4cd 100644 --- a/docs/reference/create_series.html +++ b/docs/reference/create_series.html @@ -8,21 +8,25 @@ Create a <code>tbl_time</code> object with a sequence of regularly spaced dates — create_series • tibbletime + - + + - + - + + - + - - + + + @@ -30,16 +34,18 @@ - + + - + + +
    @@ -136,15 +143,13 @@

    Create a tbl_time object with a sequence of regularly spaced da

    -

    create_series() allows the user to quickly create a tbl_time object with a date column populated with a sequence of dates.

    - 
    create_series(time_formula, period = "daily", class = "POSIXct",
   include_end = FALSE, tz = "UTC", as_vector = FALSE)
    - +

    Arguments

    @@ -189,188 +194,188 @@

    Arg a tibble?

    - +

    Examples

    
 # Every day in 2013
 create_series(~'2013', 'daily')
    #> # A time tibble: 365 x 1
-#> # Index: date
+#> # Index: date
 #>    date               
-#>    <dttm>             
-#>  1 2013-01-01 00:00:00
-#>  2 2013-01-02 00:00:00
-#>  3 2013-01-03 00:00:00
-#>  4 2013-01-04 00:00:00
-#>  5 2013-01-05 00:00:00
-#>  6 2013-01-06 00:00:00
-#>  7 2013-01-07 00:00:00
-#>  8 2013-01-08 00:00:00
-#>  9 2013-01-09 00:00:00
-#> 10 2013-01-10 00:00:00
-#> # … with 355 more rows
    
+#>    <dttm>             
+#>  1 2013-01-01 00:00:00
+#>  2 2013-01-02 00:00:00
+#>  3 2013-01-03 00:00:00
+#>  4 2013-01-04 00:00:00
+#>  5 2013-01-05 00:00:00
+#>  6 2013-01-06 00:00:00
+#>  7 2013-01-07 00:00:00
+#>  8 2013-01-08 00:00:00
+#>  9 2013-01-09 00:00:00
+#> 10 2013-01-10 00:00:00
+#> # … with 355 more rows
    
 # Every other day in 2013
 create_series(~'2013', '2 d')
    #> # A time tibble: 183 x 1
-#> # Index: date
+#> # Index: date
 #>    date               
-#>    <dttm>             
-#>  1 2013-01-01 00:00:00
-#>  2 2013-01-03 00:00:00
-#>  3 2013-01-05 00:00:00
-#>  4 2013-01-07 00:00:00
-#>  5 2013-01-09 00:00:00
-#>  6 2013-01-11 00:00:00
-#>  7 2013-01-13 00:00:00
-#>  8 2013-01-15 00:00:00
-#>  9 2013-01-17 00:00:00
-#> 10 2013-01-19 00:00:00
-#> # … with 173 more rows
    
+#>    <dttm>             
+#>  1 2013-01-01 00:00:00
+#>  2 2013-01-03 00:00:00
+#>  3 2013-01-05 00:00:00
+#>  4 2013-01-07 00:00:00
+#>  5 2013-01-09 00:00:00
+#>  6 2013-01-11 00:00:00
+#>  7 2013-01-13 00:00:00
+#>  8 2013-01-15 00:00:00
+#>  9 2013-01-17 00:00:00
+#> 10 2013-01-19 00:00:00
+#> # … with 173 more rows
    
 # Every quarter in 2013
 create_series(~'2013', '1 q')
    #> # A time tibble: 4 x 1
-#> # Index: date
+#> # Index: date
 #>   date               
-#>   <dttm>             
-#> 1 2013-01-01 00:00:00
-#> 2 2013-04-01 00:00:00
-#> 3 2013-07-01 00:00:00
-#> 4 2013-10-01 00:00:00
    
+#>   <dttm>             
+#> 1 2013-01-01 00:00:00
+#> 2 2013-04-01 00:00:00
+#> 3 2013-07-01 00:00:00
+#> 4 2013-10-01 00:00:00
    
 # Daily series for 2013-2015
 create_series('2013' ~ '2015', '1 d')
    #> # A time tibble: 1,095 x 1
-#> # Index: date
+#> # Index: date
 #>    date               
-#>    <dttm>             
-#>  1 2013-01-01 00:00:00
-#>  2 2013-01-02 00:00:00
-#>  3 2013-01-03 00:00:00
-#>  4 2013-01-04 00:00:00
-#>  5 2013-01-05 00:00:00
-#>  6 2013-01-06 00:00:00
-#>  7 2013-01-07 00:00:00
-#>  8 2013-01-08 00:00:00
-#>  9 2013-01-09 00:00:00
-#> 10 2013-01-10 00:00:00
-#> # … with 1,085 more rows
    
+#>    <dttm>             
+#>  1 2013-01-01 00:00:00
+#>  2 2013-01-02 00:00:00
+#>  3 2013-01-03 00:00:00
+#>  4 2013-01-04 00:00:00
+#>  5 2013-01-05 00:00:00
+#>  6 2013-01-06 00:00:00
+#>  7 2013-01-07 00:00:00
+#>  8 2013-01-08 00:00:00
+#>  9 2013-01-09 00:00:00
+#> 10 2013-01-10 00:00:00
+#> # … with 1,085 more rows
    
 # Minute series for 2 months
 create_series('2012-01' ~ '2012-02', 'M')
    #> # A time tibble: 86,400 x 1
-#> # Index: date
+#> # Index: date
 #>    date               
-#>    <dttm>             
-#>  1 2012-01-01 00:00:00
-#>  2 2012-01-01 00:01:00
-#>  3 2012-01-01 00:02:00
-#>  4 2012-01-01 00:03:00
-#>  5 2012-01-01 00:04:00
-#>  6 2012-01-01 00:05:00
-#>  7 2012-01-01 00:06:00
-#>  8 2012-01-01 00:07:00
-#>  9 2012-01-01 00:08:00
-#> 10 2012-01-01 00:09:00
-#> # … with 86,390 more rows
    
+#>    <dttm>             
+#>  1 2012-01-01 00:00:00
+#>  2 2012-01-01 00:01:00
+#>  3 2012-01-01 00:02:00
+#>  4 2012-01-01 00:03:00
+#>  5 2012-01-01 00:04:00
+#>  6 2012-01-01 00:05:00
+#>  7 2012-01-01 00:06:00
+#>  8 2012-01-01 00:07:00
+#>  9 2012-01-01 00:08:00
+#> 10 2012-01-01 00:09:00
+#> # … with 86,390 more rows
    
 # Second series for 2 minutes
 create_series('2011-01-01 12:10:00' ~ '2011-01-01 12:12:00', 's')
    #> # A time tibble: 121 x 1
-#> # Index: date
+#> # Index: date
 #>    date               
-#>    <dttm>             
-#>  1 2011-01-01 12:10:00
-#>  2 2011-01-01 12:10:01
-#>  3 2011-01-01 12:10:02
-#>  4 2011-01-01 12:10:03
-#>  5 2011-01-01 12:10:04
-#>  6 2011-01-01 12:10:05
-#>  7 2011-01-01 12:10:06
-#>  8 2011-01-01 12:10:07
-#>  9 2011-01-01 12:10:08
-#> 10 2011-01-01 12:10:09
-#> # … with 111 more rows
    
+#>    <dttm>             
+#>  1 2011-01-01 12:10:00
+#>  2 2011-01-01 12:10:01
+#>  3 2011-01-01 12:10:02
+#>  4 2011-01-01 12:10:03
+#>  5 2011-01-01 12:10:04
+#>  6 2011-01-01 12:10:05
+#>  7 2011-01-01 12:10:06
+#>  8 2011-01-01 12:10:07
+#>  9 2011-01-01 12:10:08
+#> 10 2011-01-01 12:10:09
+#> # … with 111 more rows
    
 # Date class
 create_series(~'2013', 'day', class = "Date")
    #> # A time tibble: 365 x 1
-#> # Index: date
+#> # Index: date
 #>    date      
-#>    <date>    
-#>  1 2013-01-01
-#>  2 2013-01-02
-#>  3 2013-01-03
-#>  4 2013-01-04
-#>  5 2013-01-05
-#>  6 2013-01-06
-#>  7 2013-01-07
-#>  8 2013-01-08
-#>  9 2013-01-09
-#> 10 2013-01-10
-#> # … with 355 more rows
    
+#>    <date>    
+#>  1 2013-01-01
+#>  2 2013-01-02
+#>  3 2013-01-03
+#>  4 2013-01-04
+#>  5 2013-01-05
+#>  6 2013-01-06
+#>  7 2013-01-07
+#>  8 2013-01-08
+#>  9 2013-01-09
+#> 10 2013-01-10
+#> # … with 355 more rows
    
 # yearmon class
 create_series(~'2013', 'month', class = "yearmon")
    #> # A time tibble: 12 x 1
-#> # Index: date
-#>    date         
-#>    <S3: yearmon>
-#>  1 Jan 2013     
-#>  2 Feb 2013     
-#>  3 Mar 2013     
-#>  4 Apr 2013     
-#>  5 May 2013     
-#>  6 Jun 2013     
-#>  7 Jul 2013     
-#>  8 Aug 2013     
-#>  9 Sep 2013     
-#> 10 Oct 2013     
-#> 11 Nov 2013     
-#> 12 Dec 2013     
    
+#> # Index: date
+#>    date     
+#>    <yearmon>
+#>  1 Jan 2013 
+#>  2 Feb 2013 
+#>  3 Mar 2013 
+#>  4 Apr 2013 
+#>  5 May 2013 
+#>  6 Jun 2013 
+#>  7 Jul 2013 
+#>  8 Aug 2013 
+#>  9 Sep 2013 
+#> 10 Oct 2013 
+#> 11 Nov 2013 
+#> 12 Dec 2013 
    
 # hms class. time_formula specified as HH:MM:SS here
 create_series('00:00:00' ~ '12:00:00', 'second' , class = "hms")
    #> # A time tibble: 43,201 x 1
-#> # Index: date
+#> # Index: date
 #>    date  
-#>    <time>
-#>  1 00'00"
-#>  2 00'01"
-#>  3 00'02"
-#>  4 00'03"
-#>  5 00'04"
-#>  6 00'05"
-#>  7 00'06"
-#>  8 00'07"
-#>  9 00'08"
-#> 10 00'09"
-#> # … with 43,191 more rows
    
+#>    <time>
+#>  1 00'00"
+#>  2 00'01"
+#>  3 00'02"
+#>  4 00'03"
+#>  5 00'04"
+#>  6 00'05"
+#>  7 00'06"
+#>  8 00'07"
+#>  9 00'08"
+#> 10 00'09"
+#> # … with 43,191 more rows
    
 # Subsecond series
 create_series('2013' ~ '2013-01-01 00:00:01', period = "10 millisec")
    #> # A time tibble: 101 x 1
-#> # Index: date
+#> # Index: date
 #>    date               
-#>    <dttm>             
-#>  1 2013-01-01 00:00:00
-#>  2 2013-01-01 00:00:00
-#>  3 2013-01-01 00:00:00
-#>  4 2013-01-01 00:00:00
-#>  5 2013-01-01 00:00:00
-#>  6 2013-01-01 00:00:00
-#>  7 2013-01-01 00:00:00
-#>  8 2013-01-01 00:00:00
-#>  9 2013-01-01 00:00:00
-#> 10 2013-01-01 00:00:00
-#> # … with 91 more rows
    milli <- create_series('2013' ~ '2013-01-01 00:00:01', period = ".1 sec")
+#>    <dttm>             
+#>  1 2013-01-01 00:00:00
+#>  2 2013-01-01 00:00:00
+#>  3 2013-01-01 00:00:00
+#>  4 2013-01-01 00:00:00
+#>  5 2013-01-01 00:00:00
+#>  6 2013-01-01 00:00:00
+#>  7 2013-01-01 00:00:00
+#>  8 2013-01-01 00:00:00
+#>  9 2013-01-01 00:00:00
+#> 10 2013-01-01 00:00:00
+#> # … with 91 more rows
    milli <- create_series('2013' ~ '2013-01-01 00:00:01', period = ".1 sec")
 # Check that 'milli' is correct by running:
 # options("digits.secs" = 4)
 # options("digits" = 18)
 # milli$date
-# as.numeric(milli$date)
    +# as.numeric(milli$date) + @@ -378,6 +383,8 @@

    Contents

    + + diff --git a/docs/reference/filter_time.html b/docs/reference/filter_time.html index c903ee8..4a64a75 100644 --- a/docs/reference/filter_time.html +++ b/docs/reference/filter_time.html @@ -8,21 +8,25 @@ Succinctly filter a <code>tbl_time</code> object by its index — filter_time • tibbletime + - + + - + - + + - + - - + + + @@ -30,15 +34,17 @@ - + + - + + +
    @@ -135,16 +142,14 @@

    Succinctly filter a tbl_time object by its index

    -

    Use a concise filtering method to filter a tbl_time object by its index.

    - 
    filter_time(.tbl_time, time_formula)
 
 # S3 method for tbl_time
 [(x, i, j, drop = FALSE)
    - +

    Arguments

    @@ -176,221 +181,225 @@

    Arg

    Will always be coerced to FALSE by tibble.
    - +

    Details

    -

    The time_formula is specified using the format from ~ to. +

    The time_formula is specified using the format from ~ to. Each side of the time_formula is specified as the character 'YYYY-MM-DD HH:MM:SS', but powerful shorthand is available. Some examples are:

    -

    The time_formula can also use a one sided formula.

    + @@ -189,6 +195,8 @@

    Contents

    + + diff --git a/docs/reference/reconstruct.html b/docs/reference/reconstruct.html index d1f400f..be1fdba 100644 --- a/docs/reference/reconstruct.html +++ b/docs/reference/reconstruct.html @@ -8,21 +8,25 @@ Reconstruct an S3 class from a template — reconstruct • tibbletime + - + + - + - + + - + - - + + + @@ -30,8 +34,8 @@ - + @@ -39,8 +43,10 @@ + - + + +
    @@ -137,15 +144,13 @@

    Reconstruct an S3 class from a template

    -

    This is an implementation of sloop::reconstruct() that users can ignore. Once sloop is on CRAN, this function will be removed and that version will be used. It currently must be exported for use in tidyquant.

    - 
    reconstruct(new, old)
    - +

    Arguments

    @@ -158,25 +163,26 @@

    Arg

    Existing object to use as template
    - + + @@ -184,6 +190,8 @@

    Contents

    + + diff --git a/docs/reference/reexports.html b/docs/reference/reexports.html index 5443308..8c0e97a 100644 --- a/docs/reference/reexports.html +++ b/docs/reference/reexports.html @@ -8,21 +8,25 @@ Objects exported from other packages — reexports • tibbletime + - + + - + - + + - + - - + + + @@ -30,19 +34,22 @@ - + + - + + +
    @@ -139,33 +147,34 @@

    Objects exported from other packages

    -

    These objects are imported from other packages. Follow the links below to see their documentation.

    dplyr

    filter, %>%

    +
    -
    - + + + @@ -173,6 +182,8 @@

    Contents

    + + diff --git a/docs/reference/rollify.html b/docs/reference/rollify.html index 1381ef0..d46634e 100644 --- a/docs/reference/rollify.html +++ b/docs/reference/rollify.html @@ -8,21 +8,25 @@ Create a rolling version of any function — rollify • tibbletime + - + + - + - + + - + - - + + + @@ -30,16 +34,18 @@ - + + - + + +
    @@ -136,14 +143,12 @@

    Create a rolling version of any function

    -

    rollify returns a rolling version of the input function, with a rolling window specified by the user.

    - 
    rollify(.f, window = 1, unlist = TRUE, na_value = NULL)
    - +

    Arguments

    @@ -151,7 +156,7 @@

    Arg

    @@ -182,7 +187,7 @@

    Arg roll.

    .f

    A function, formula, or vector (not necessarily atomic).

    If a function, it is used as is.

    -

    If a formula, e.g. ~ .x + 2, it is converted to a function. There +

    If a formula, e.g. ~ .x + 2, it is converted to a function. There are three ways to refer to the arguments:

    • For a single argument function, use .

    • For a two argument function, use .x and .y

      • @@ -172,8 +177,8 @@

      Arg

    unlist

    If the function returns a single value each time it is called, -use unlist = TRUE. If the function returns more than one value, or a more -complicated object (like a linear model), use unlist = FALSE to create +use unlist = TRUE. If the function returns more than one value, or a more +complicated object (like a linear model), use unlist = FALSE to create a list-column of the rolling results.
    - +

    Details

    The intended use of rollify is to turn a function into a rolling version @@ -199,126 +204,124 @@

    Details

    If optional arguments to the function are required, specify them in the call to rollify, and not in the call to the rolling version of the function. See the examples for more details.

    -

    See also

    purrr::safely, purrr::possibly

    -

    Examples

    
 # Rolling mean --------------------------------------------------------------
 
-data(FB)
+data(FB)
 
 # Turn the normal mean function into a rolling mean with a 5 row window
 mean_roll_5 <- rollify(mean, window = 5)
 
 dplyr::mutate(FB,
-       normal_mean  = mean(adjusted),
-       rolling_mean = mean_roll_5(adjusted))
    #> # A tibble: 1,008 x 10
+       normal_mean  = mean(adjusted),
+       rolling_mean = mean_roll_5(adjusted))
    #> # A tibble: 1,008 x 10
 #>    symbol date        open  high   low close volume adjusted normal_mean
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>  <dbl>    <dbl>       <dbl>
-#>  1 FB     2013-01-02  27.4  28.2  27.4  28   6.98e7     28          77.5
-#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8 6.31e7     27.8        77.5
-#>  3 FB     2013-01-04  28.0  28.9  27.8  28.8 7.27e7     28.8        77.5
-#>  4 FB     2013-01-07  28.7  29.8  28.6  29.4 8.38e7     29.4        77.5
-#>  5 FB     2013-01-08  29.5  29.6  28.9  29.1 4.59e7     29.1        77.5
-#>  6 FB     2013-01-09  29.7  30.6  29.5  30.6 1.05e8     30.6        77.5
-#>  7 FB     2013-01-10  30.6  31.5  30.3  31.3 9.53e7     31.3        77.5
-#>  8 FB     2013-01-11  31.3  32.0  31.1  31.7 8.96e7     31.7        77.5
-#>  9 FB     2013-01-14  32.1  32.2  30.6  31.0 9.89e7     31.0        77.5
-#> 10 FB     2013-01-15  30.6  31.7  29.9  30.1 1.73e8     30.1        77.5
-#> # … with 998 more rows, and 1 more variable: rolling_mean <dbl>
    
+#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>  <dbl>    <dbl>       <dbl>
+#>  1 FB     2013-01-02  27.4  28.2  27.4  28   6.98e7     28          77.5
+#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8 6.31e7     27.8        77.5
+#>  3 FB     2013-01-04  28.0  28.9  27.8  28.8 7.27e7     28.8        77.5
+#>  4 FB     2013-01-07  28.7  29.8  28.6  29.4 8.38e7     29.4        77.5
+#>  5 FB     2013-01-08  29.5  29.6  28.9  29.1 4.59e7     29.1        77.5
+#>  6 FB     2013-01-09  29.7  30.6  29.5  30.6 1.05e8     30.6        77.5
+#>  7 FB     2013-01-10  30.6  31.5  30.3  31.3 9.53e7     31.3        77.5
+#>  8 FB     2013-01-11  31.3  32.0  31.1  31.7 8.96e7     31.7        77.5
+#>  9 FB     2013-01-14  32.1  32.2  30.6  31.0 9.89e7     31.0        77.5
+#> 10 FB     2013-01-15  30.6  31.7  29.9  30.1 1.73e8     30.1        77.5
+#> # … with 998 more rows, and 1 more variable: rolling_mean <dbl>
    
 # There's nothing stopping you from combining multiple rolling functions with
 # different window sizes in the same mutate call
 mean_roll_10 <- rollify(mean, window = 10)
 
 dplyr::mutate(FB,
        rolling_mean_5  = mean_roll_5(adjusted),
-       rolling_mean_10 = mean_roll_10(adjusted))
    #> # A tibble: 1,008 x 10
+       rolling_mean_10 = mean_roll_10(adjusted))
    #> # A tibble: 1,008 x 10
 #>    symbol date        open  high   low close volume adjusted rolling_mean_5
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>  <dbl>    <dbl>          <dbl>
-#>  1 FB     2013-01-02  27.4  28.2  27.4  28   6.98e7     28             NA  
-#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8 6.31e7     27.8           NA  
-#>  3 FB     2013-01-04  28.0  28.9  27.8  28.8 7.27e7     28.8           NA  
-#>  4 FB     2013-01-07  28.7  29.8  28.6  29.4 8.38e7     29.4           NA  
-#>  5 FB     2013-01-08  29.5  29.6  28.9  29.1 4.59e7     29.1           28.6
-#>  6 FB     2013-01-09  29.7  30.6  29.5  30.6 1.05e8     30.6           29.1
-#>  7 FB     2013-01-10  30.6  31.5  30.3  31.3 9.53e7     31.3           29.8
-#>  8 FB     2013-01-11  31.3  32.0  31.1  31.7 8.96e7     31.7           30.4
-#>  9 FB     2013-01-14  32.1  32.2  30.6  31.0 9.89e7     31.0           30.7
-#> 10 FB     2013-01-15  30.6  31.7  29.9  30.1 1.73e8     30.1           30.9
-#> # … with 998 more rows, and 1 more variable: rolling_mean_10 <dbl>
    
+#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>  <dbl>    <dbl>          <dbl>
+#>  1 FB     2013-01-02  27.4  28.2  27.4  28   6.98e7     28             NA  
+#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8 6.31e7     27.8           NA  
+#>  3 FB     2013-01-04  28.0  28.9  27.8  28.8 7.27e7     28.8           NA  
+#>  4 FB     2013-01-07  28.7  29.8  28.6  29.4 8.38e7     29.4           NA  
+#>  5 FB     2013-01-08  29.5  29.6  28.9  29.1 4.59e7     29.1           28.6
+#>  6 FB     2013-01-09  29.7  30.6  29.5  30.6 1.05e8     30.6           29.1
+#>  7 FB     2013-01-10  30.6  31.5  30.3  31.3 9.53e7     31.3           29.8
+#>  8 FB     2013-01-11  31.3  32.0  31.1  31.7 8.96e7     31.7           30.4
+#>  9 FB     2013-01-14  32.1  32.2  30.6  31.0 9.89e7     31.0           30.7
+#> 10 FB     2013-01-15  30.6  31.7  29.9  30.1 1.73e8     30.1           30.9
+#> # … with 998 more rows, and 1 more variable: rolling_mean_10 <dbl>
    
 # Functions with multiple args and optional args ----------------------------
 
 # With 2 args, use the purrr syntax of ~ and .x, .y
 # Rolling correlation example
-cor_roll <- rollify(~cor(.x, .y), window = 5)
+cor_roll <- rollify(~cor(.x, .y), window = 5)
 
-dplyr::mutate(FB, running_cor = cor_roll(adjusted, open))
    #> # A tibble: 1,008 x 9
+dplyr::mutate(FB, running_cor = cor_roll(adjusted, open))
    #> # A tibble: 1,008 x 9
 #>    symbol date        open  high   low close    volume adjusted running_cor
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>       <dbl>
-#>  1 FB     2013-01-02  27.4  28.2  27.4  28    69846400     28        NA    
-#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8  63140600     27.8      NA    
-#>  3 FB     2013-01-04  28.0  28.9  27.8  28.8  72715400     28.8      NA    
-#>  4 FB     2013-01-07  28.7  29.8  28.6  29.4  83781800     29.4      NA    
-#>  5 FB     2013-01-08  29.5  29.6  28.9  29.1  45871300     29.1       0.749
-#>  6 FB     2013-01-09  29.7  30.6  29.5  30.6 104787700     30.6       0.805
-#>  7 FB     2013-01-10  30.6  31.5  30.3  31.3  95316400     31.3       0.859
-#>  8 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7       0.884
-#>  9 FB     2013-01-14  32.1  32.2  30.6  31.0  98892800     31.0       0.667
-#> 10 FB     2013-01-15  30.6  31.7  29.9  30.1 173242600     30.1       0.379
-#> # … with 998 more rows
    
+#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>       <dbl>
+#>  1 FB     2013-01-02  27.4  28.2  27.4  28    69846400     28        NA    
+#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8  63140600     27.8      NA    
+#>  3 FB     2013-01-04  28.0  28.9  27.8  28.8  72715400     28.8      NA    
+#>  4 FB     2013-01-07  28.7  29.8  28.6  29.4  83781800     29.4      NA    
+#>  5 FB     2013-01-08  29.5  29.6  28.9  29.1  45871300     29.1       0.749
+#>  6 FB     2013-01-09  29.7  30.6  29.5  30.6 104787700     30.6       0.805
+#>  7 FB     2013-01-10  30.6  31.5  30.3  31.3  95316400     31.3       0.859
+#>  8 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7       0.884
+#>  9 FB     2013-01-14  32.1  32.2  30.6  31.0  98892800     31.0       0.667
+#> 10 FB     2013-01-15  30.6  31.7  29.9  30.1 173242600     30.1       0.379
+#> # … with 998 more rows
    
 # With >2 args, create an anonymous function with >2 args or use
 # the purrr convention of ..1, ..2, ..3 to refer to the arguments
 avg_of_avgs <- rollify(function(x, y, z) {
-                         (mean(x) + mean(y) + mean(z)) / 3
+                         (mean(x) + mean(y) + mean(z)) / 3
                        },
                        window = 10)
 
 # Or
-avg_of_avgs <- rollify(~(mean(..1) + mean(..2) + mean(..3)) / 3,
+avg_of_avgs <- rollify(~(mean(..1) + mean(..2) + mean(..3)) / 3,
                        window = 10)
 
-dplyr::mutate(FB, avg_of_avgs = avg_of_avgs(open, high, low))
    #> # A tibble: 1,008 x 9
+dplyr::mutate(FB, avg_of_avgs = avg_of_avgs(open, high, low))
    #> # A tibble: 1,008 x 9
 #>    symbol date        open  high   low close    volume adjusted avg_of_avgs
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>       <dbl>
-#>  1 FB     2013-01-02  27.4  28.2  27.4  28    69846400     28          NA  
-#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8  63140600     27.8        NA  
-#>  3 FB     2013-01-04  28.0  28.9  27.8  28.8  72715400     28.8        NA  
-#>  4 FB     2013-01-07  28.7  29.8  28.6  29.4  83781800     29.4        NA  
-#>  5 FB     2013-01-08  29.5  29.6  28.9  29.1  45871300     29.1        NA  
-#>  6 FB     2013-01-09  29.7  30.6  29.5  30.6 104787700     30.6        NA  
-#>  7 FB     2013-01-10  30.6  31.5  30.3  31.3  95316400     31.3        NA  
-#>  8 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7        NA  
-#>  9 FB     2013-01-14  32.1  32.2  30.6  31.0  98892800     31.0        NA  
-#> 10 FB     2013-01-15  30.6  31.7  29.9  30.1 173242600     30.1        29.7
-#> # … with 998 more rows
    
+#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>       <dbl>
+#>  1 FB     2013-01-02  27.4  28.2  27.4  28    69846400     28          NA  
+#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8  63140600     27.8        NA  
+#>  3 FB     2013-01-04  28.0  28.9  27.8  28.8  72715400     28.8        NA  
+#>  4 FB     2013-01-07  28.7  29.8  28.6  29.4  83781800     29.4        NA  
+#>  5 FB     2013-01-08  29.5  29.6  28.9  29.1  45871300     29.1        NA  
+#>  6 FB     2013-01-09  29.7  30.6  29.5  30.6 104787700     30.6        NA  
+#>  7 FB     2013-01-10  30.6  31.5  30.3  31.3  95316400     31.3        NA  
+#>  8 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7        NA  
+#>  9 FB     2013-01-14  32.1  32.2  30.6  31.0  98892800     31.0        NA  
+#> 10 FB     2013-01-15  30.6  31.7  29.9  30.1 173242600     30.1        29.7
+#> # … with 998 more rows
    
 # Optional arguments MUST be passed at the creation of the rolling function
 # Only data arguments that are "rolled over" are allowed when calling the
 # rolling version of the function
 FB$adjusted[1] <- NA
 
-roll_mean_na_rm <- rollify(~mean(.x, na.rm = TRUE), window = 5)
+roll_mean_na_rm <- rollify(~mean(.x, na.rm = TRUE), window = 5)
 
-dplyr::mutate(FB, roll_mean = roll_mean_na_rm(adjusted))
    #> # A tibble: 1,008 x 9
+dplyr::mutate(FB, roll_mean = roll_mean_na_rm(adjusted))
    #> # A tibble: 1,008 x 9
 #>    symbol date        open  high   low close    volume adjusted roll_mean
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>     <dbl>
-#>  1 FB     2013-01-02  27.4  28.2  27.4  28    69846400     NA        NA  
-#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8  63140600     27.8      NA  
-#>  3 FB     2013-01-04  28.0  28.9  27.8  28.8  72715400     28.8      NA  
-#>  4 FB     2013-01-07  28.7  29.8  28.6  29.4  83781800     29.4      NA  
-#>  5 FB     2013-01-08  29.5  29.6  28.9  29.1  45871300     29.1      28.8
-#>  6 FB     2013-01-09  29.7  30.6  29.5  30.6 104787700     30.6      29.1
-#>  7 FB     2013-01-10  30.6  31.5  30.3  31.3  95316400     31.3      29.8
-#>  8 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7      30.4
-#>  9 FB     2013-01-14  32.1  32.2  30.6  31.0  98892800     31.0      30.7
-#> 10 FB     2013-01-15  30.6  31.7  29.9  30.1 173242600     30.1      30.9
-#> # … with 998 more rows
    
+#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>     <dbl>
+#>  1 FB     2013-01-02  27.4  28.2  27.4  28    69846400     NA        NA  
+#>  2 FB     2013-01-03  27.9  28.5  27.6  27.8  63140600     27.8      NA  
+#>  3 FB     2013-01-04  28.0  28.9  27.8  28.8  72715400     28.8      NA  
+#>  4 FB     2013-01-07  28.7  29.8  28.6  29.4  83781800     29.4      NA  
+#>  5 FB     2013-01-08  29.5  29.6  28.9  29.1  45871300     29.1      28.8
+#>  6 FB     2013-01-09  29.7  30.6  29.5  30.6 104787700     30.6      29.1
+#>  7 FB     2013-01-10  30.6  31.5  30.3  31.3  95316400     31.3      29.8
+#>  8 FB     2013-01-11  31.3  32.0  31.1  31.7  89598000     31.7      30.4
+#>  9 FB     2013-01-14  32.1  32.2  30.6  31.0  98892800     31.0      30.7
+#> 10 FB     2013-01-15  30.6  31.7  29.9  30.1 173242600     30.1      30.9
+#> # … with 998 more rows
    
 # Returning multiple values -------------------------------------------------
 
-data(FB)
+data(FB)
 
 # If the function returns >1 value, set the `unlist = FALSE` argument
 # Running 5 number summary
@@ -330,57 +333,57 @@ 
    Examp
 # dplyr::bind_rows() is often helpful in these cases to get
 # meaningful output
 
-summary_roll <- rollify(~dplyr::bind_rows(summary(.)), window = 5, unlist = FALSE)
+summary_roll <- rollify(~dplyr::bind_rows(summary(.)), window = 5, unlist = FALSE)
 FB_summarised <- dplyr::mutate(FB, summary_roll = summary_roll(adjusted))
 FB_summarised %>%
-  dplyr::filter(!is.na(summary_roll)) %>%
-  tidyr::unnest(summary_roll)
    #> # A tibble: 1,004 x 15
+  dplyr::filter(!is.na(summary_roll)) %>%
+  tidyr::unnest(summary_roll)
    #> # A tibble: 1,004 x 15
 #>    symbol date        open  high   low close volume adjusted  Min. `1st Qu.`
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>  <dbl>    <dbl> <dbl>     <dbl>
-#>  1 FB     2013-01-08  29.5  29.6  28.9  29.1 4.59e7     29.1  27.8      28.5
-#>  2 FB     2013-01-09  29.7  30.6  29.5  30.6 1.05e8     30.6  27.8      28.8
-#>  3 FB     2013-01-10  30.6  31.5  30.3  31.3 9.53e7     31.3  28.8      29.1
-#>  4 FB     2013-01-11  31.3  32.0  31.1  31.7 8.96e7     31.7  29.1      29.4
-#>  5 FB     2013-01-14  32.1  32.2  30.6  31.0 9.89e7     31.0  29.1      30.6
-#>  6 FB     2013-01-15  30.6  31.7  29.9  30.1 1.73e8     30.1  30.1      30.6
-#>  7 FB     2013-01-16  30.2  30.4  29.5  29.8 7.53e7     29.8  29.8      30.1
-#>  8 FB     2013-01-17  30.1  30.4  30.0  30.1 4.03e7     30.1  29.8      30.1
-#>  9 FB     2013-01-18  30.3  30.4  29.3  29.7 4.96e7     29.7  29.7      29.8
-#> 10 FB     2013-01-22  29.8  30.9  29.7  30.7 5.52e7     30.7  29.7      29.8
-#> # … with 994 more rows, and 5 more variables: Median <dbl>, Mean <dbl>, `3rd
-#> #   Qu.` <dbl>, Max. <dbl>, `NA's` <dbl>
    
+#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>  <dbl>    <dbl> <dbl>     <dbl>
+#>  1 FB     2013-01-08  29.5  29.6  28.9  29.1 4.59e7     29.1  27.8      28.5
+#>  2 FB     2013-01-09  29.7  30.6  29.5  30.6 1.05e8     30.6  27.8      28.8
+#>  3 FB     2013-01-10  30.6  31.5  30.3  31.3 9.53e7     31.3  28.8      29.1
+#>  4 FB     2013-01-11  31.3  32.0  31.1  31.7 8.96e7     31.7  29.1      29.4
+#>  5 FB     2013-01-14  32.1  32.2  30.6  31.0 9.89e7     31.0  29.1      30.6
+#>  6 FB     2013-01-15  30.6  31.7  29.9  30.1 1.73e8     30.1  30.1      30.6
+#>  7 FB     2013-01-16  30.2  30.4  29.5  29.8 7.53e7     29.8  29.8      30.1
+#>  8 FB     2013-01-17  30.1  30.4  30.0  30.1 4.03e7     30.1  29.8      30.1
+#>  9 FB     2013-01-18  30.3  30.4  29.3  29.7 4.96e7     29.7  29.7      29.8
+#> 10 FB     2013-01-22  29.8  30.9  29.7  30.7 5.52e7     30.7  29.7      29.8
+#> # … with 994 more rows, and 5 more variables: Median <dbl>, Mean <dbl>, `3rd
+#> #   Qu.` <dbl>, Max. <dbl>, `NA's` <dbl>
    
 # Rolling regressions -------------------------------------------------------
 
 # Extending an example from R 4 Data Science on "Many Models".
 # For each country in the gapminder data, calculate a linear regression
 # every 5 periods of lifeExp ~ year
-library(gapminder)
+library(gapminder)
 
 # Rolling regressions are easy to implement
-lm_roll <- rollify(~lm(.x ~ .y), window = 5, unlist = FALSE)
+lm_roll <- rollify(~lm(.x ~ .y), window = 5, unlist = FALSE)
 
 gapminder %>%
   dplyr::group_by(country) %>%
-  dplyr::mutate(rolling_lm = lm_roll(lifeExp, year))
    #> # A tibble: 1,704 x 7
-#> # Groups:   country [142]
+  dplyr::mutate(rolling_lm = lm_roll(lifeExp, year))
    #> # A tibble: 1,704 x 7
+#> # Groups:   country [142]
 #>    country     continent  year lifeExp      pop gdpPercap rolling_lm
-#>    <fct>       <fct>     <int>   <dbl>    <int>     <dbl> <list>    
-#>  1 Afghanistan Asia       1952    28.8  8425333      779. <lgl [1]> 
-#>  2 Afghanistan Asia       1957    30.3  9240934      821. <lgl [1]> 
-#>  3 Afghanistan Asia       1962    32.0 10267083      853. <lgl [1]> 
-#>  4 Afghanistan Asia       1967    34.0 11537966      836. <lgl [1]> 
-#>  5 Afghanistan Asia       1972    36.1 13079460      740. <S3: lm>  
-#>  6 Afghanistan Asia       1977    38.4 14880372      786. <S3: lm>  
-#>  7 Afghanistan Asia       1982    39.9 12881816      978. <S3: lm>  
-#>  8 Afghanistan Asia       1987    40.8 13867957      852. <S3: lm>  
-#>  9 Afghanistan Asia       1992    41.7 16317921      649. <S3: lm>  
-#> 10 Afghanistan Asia       1997    41.8 22227415      635. <S3: lm>  
-#> # … with 1,694 more rows
    
+#>    <fct>       <fct>     <int>   <dbl>    <int>     <dbl> <list>    
+#>  1 Afghanistan Asia       1952    28.8  8425333      779. <lgl [1]> 
+#>  2 Afghanistan Asia       1957    30.3  9240934      821. <lgl [1]> 
+#>  3 Afghanistan Asia       1962    32.0 10267083      853. <lgl [1]> 
+#>  4 Afghanistan Asia       1967    34.0 11537966      836. <lgl [1]> 
+#>  5 Afghanistan Asia       1972    36.1 13079460      740. <lm>      
+#>  6 Afghanistan Asia       1977    38.4 14880372      786. <lm>      
+#>  7 Afghanistan Asia       1982    39.9 12881816      978. <lm>      
+#>  8 Afghanistan Asia       1987    40.8 13867957      852. <lm>      
+#>  9 Afghanistan Asia       1992    41.7 16317921      649. <lm>      
+#> 10 Afghanistan Asia       1997    41.8 22227415      635. <lm>      
+#> # … with 1,694 more rows
    
 # Rolling with groups -------------------------------------------------------
 
 # One of the most powerful things about this is that it works with
 # groups since `mutate` is being used
-data(FANG)
+data(FANG)
 FANG <- FANG %>%
   dplyr::group_by(symbol)
 
@@ -388,54 +391,52 @@ 
    Examp
 
 FANG %>%
   dplyr::mutate(mean_roll = mean_roll_3(adjusted)) %>%
-  dplyr::slice(1:5)
    #> # A tibble: 20 x 9
-#> # Groups:   symbol [4]
+  dplyr::slice(1:5)
    #> # A tibble: 20 x 9
+#> # Groups:   symbol [4]
 #>    symbol date        open  high   low close   volume adjusted mean_roll
-#>    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>     <dbl>
-#>  1 AMZN   2013-01-02 256.  258.  253.  257.   3271000    257.       NA  
-#>  2 AMZN   2013-01-03 257.  261.  256.  258.   2750900    258.       NA  
-#>  3 AMZN   2013-01-04 258.  260.  257.  259.   1874200    259.      258. 
-#>  4 AMZN   2013-01-07 263.  270.  263.  268.   4910000    268.      262. 
-#>  5 AMZN   2013-01-08 267.  269.  264.  266.   3010700    266.      265. 
-#>  6 FB     2013-01-02  27.4  28.2  27.4  28   69846400     28        NA  
-#>  7 FB     2013-01-03  27.9  28.5  27.6  27.8 63140600     27.8      NA  
-#>  8 FB     2013-01-04  28.0  28.9  27.8  28.8 72715400     28.8      28.2
-#>  9 FB     2013-01-07  28.7  29.8  28.6  29.4 83781800     29.4      28.6
-#> 10 FB     2013-01-08  29.5  29.6  28.9  29.1 45871300     29.1      29.1
-#> 11 GOOG   2013-01-02 719.  727.  717.  723.   5101500    361.       NA  
-#> 12 GOOG   2013-01-03 725.  732.  721.  724.   4653700    361.       NA  
-#> 13 GOOG   2013-01-04 729.  741.  728.  738.   5547600    369.      364. 
-#> 14 GOOG   2013-01-07 735.  739.  731.  735.   3323800    367.      366. 
-#> 15 GOOG   2013-01-08 736.  736.  724.  733.   3364700    366.      367. 
-#> 16 NFLX   2013-01-02  95.2  95.8  90.7  92.0 19431300     13.1      NA  
-#> 17 NFLX   2013-01-03  92.0  97.9  91.5  96.6 27912500     13.8      NA  
-#> 18 NFLX   2013-01-04  96.5  97.7  95.5  96.0 17761100     13.7      13.6
-#> 19 NFLX   2013-01-07  96.4 102.   96.1  99.2 45550400     14.2      13.9
-#> 20 NFLX   2013-01-08 100.  101.   96.8  97.2 24714900     13.9      13.9
    
-
    +#> <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 AMZN 2013-01-02 256. 258. 253. 257. 3271000 257. NA +#> 2 AMZN 2013-01-03 257. 261. 256. 258. 2750900 258. NA +#> 3 AMZN 2013-01-04 258. 260. 257. 259. 1874200 259. 258. +#> 4 AMZN 2013-01-07 263. 270. 263. 268. 4910000 268. 262. +#> 5 AMZN 2013-01-08 267. 269. 264. 266. 3010700 266. 265. +#> 6 FB 2013-01-02 27.4 28.2 27.4 28 69846400 28 NA +#> 7 FB 2013-01-03 27.9 28.5 27.6 27.8 63140600 27.8 NA +#> 8 FB 2013-01-04 28.0 28.9 27.8 28.8 72715400 28.8 28.2 +#> 9 FB 2013-01-07 28.7 29.8 28.6 29.4 83781800 29.4 28.6 +#> 10 FB 2013-01-08 29.5 29.6 28.9 29.1 45871300 29.1 29.1 +#> 11 GOOG 2013-01-02 719. 727. 717. 723. 5101500 361. NA +#> 12 GOOG 2013-01-03 725. 732. 721. 724. 4653700 361. NA +#> 13 GOOG 2013-01-04 729. 741. 728. 738. 5547600 369. 364. +#> 14 GOOG 2013-01-07 735. 739. 731. 735. 3323800 367. 366. +#> 15 GOOG 2013-01-08 736. 736. 724. 733. 3364700 366. 367. +#> 16 NFLX 2013-01-02 95.2 95.8 90.7 92.0 19431300 13.1 NA +#> 17 NFLX 2013-01-03 92.0 97.9 91.5 96.6 27912500 13.8 NA +#> 18 NFLX 2013-01-04 96.5 97.7 95.5 96.0 17761100 13.7 13.6 +#> 19 NFLX 2013-01-07 96.4 102. 96.1 99.2 45550400 14.2 13.9 +#> 20 NFLX 2013-01-08 100. 101. 96.8 97.2 24714900 13.9 13.9
    +
     + @@ -443,6 +444,8 @@

    Contents

    + + diff --git a/docs/reference/tbl_time.html b/docs/reference/tbl_time.html index 25ce5bf..843ef6e 100644 --- a/docs/reference/tbl_time.html +++ b/docs/reference/tbl_time.html @@ -8,21 +8,25 @@ Create <code>tbl_time</code> objects — as_tbl_time • tibbletime + - + + - + - + + - + - - + + + @@ -30,8 +34,8 @@ - + @@ -39,8 +43,10 @@ + - + + +
    @@ -137,17 +144,15 @@

    Create tbl_time objects

    -

    tbl_time objects have a time index that contains information about which column should be used for time-based subsetting and other time-based manipulation. Otherwise, they function as normal tibbles.

    - 
    as_tbl_time(x, index = NULL, ...)
 
 tbl_time(x, index = NULL)
    - +

    Arguments

    @@ -166,7 +171,7 @@

    Arg necessary first.

    - +

    Details

    The information stored about tbl_time objects are the index_quo and the @@ -176,24 +181,23 @@

    Details yearqtr, and hms have experimental support. Due to dplyr's handling of S3 classes like these 3, the classes are lost when you manipulate the index columns directly.

    -

    Examples

    
 # Converting a data.frame to a `tbl_time`
 # Using Date index
-ex1 <- data.frame(date = Sys.Date(), value = 1)
+ex1 <- data.frame(date = Sys.Date(), value = 1)
 ex1_tbl_time <- as_tbl_time(ex1, date)
-class(ex1_tbl_time)
    #> [1] "tbl_time"   "tbl_df"     "tbl"        "data.frame"
    attributes(ex1_tbl_time)
    #> $names
+class(ex1_tbl_time)
    #> [1] "tbl_time"   "tbl_df"     "tbl"        "data.frame"
    attributes(ex1_tbl_time)
    #> $names
 #> [1] "date"  "value"
 #> 
 #> $row.names
 #> [1] 1
 #> 
 #> $index_quo
-#> <quosure>
-#> expr: ^date
-#> env:  0x7fa8eb0376c8
+#> <quosure>
+#> expr: ^date
+#> env:  0x7fafa22051f8
 #> 
 #> $index_time_zone
 #> [1] "UTC"
@@ -204,37 +208,36 @@ 
    Examp
 # Converting a tibble to a `tbl_time`
 # Using POSIXct index
 ex2 <- tibble::tibble(
-  time  = as.POSIXct(c("2017-01-01 10:12:01", "2017-01-02 12:12:01")),
-  value = c(1, 2)
+  time  = as.POSIXct(c("2017-01-01 10:12:01", "2017-01-02 12:12:01")),
+  value = c(1, 2)
 )
 as_tbl_time(ex2, time)
    #> # A time tibble: 2 x 2
-#> # Index: time
+#> # Index: time
 #>   time                value
-#>   <dttm>              <dbl>
-#> 1 2017-01-01 10:12:01     1
-#> 2 2017-01-02 12:12:01     2
    
-
    +#> <dttm> <dbl> +#> 1 2017-01-01 10:12:01 1 +#> 2 2017-01-02 12:12:01 2
    +
     + @@ -242,6 +245,8 @@

    Contents

    + + diff --git a/docs/reference/tibbletime.html b/docs/reference/tibbletime.html index fc451ef..df2f836 100644 --- a/docs/reference/tibbletime.html +++ b/docs/reference/tibbletime.html @@ -8,21 +8,25 @@ tibbletime: time-aware tibbles — tibbletime • tibbletime + - + + - + - + + - + - - + + + @@ -30,8 +34,8 @@ - + + +
    @@ -140,32 +147,31 @@

    tibbletime: time-aware tibbles

    -

    Built on top of the 'tibble' package, 'tibbletime' is an extension that allows for the creation of time aware tibbles. Some immediate advantages of this include: the ability to perform time based subsetting on tibbles, quickly summarising and aggregating results by time periods, and calling functions similar in spirit to the map family from 'purrr' on time based tibbles.

    -
    - + +

    See also

    Useful links:

    - + + + + @@ -191,6 +198,8 @@

    Author

    + + diff --git a/revdep/.gitignore b/revdep/.gitignore new file mode 100644 index 0000000..31f6c40 --- /dev/null +++ b/revdep/.gitignore @@ -0,0 +1,6 @@ +checks +library +checks.noindex +library.noindex +data.sqlite +*.html diff --git a/revdep/README.md b/revdep/README.md index 16076f1..20453ac 100644 --- a/revdep/README.md +++ b/revdep/README.md @@ -2,29 +2,23 @@ |field |value | |:--------|:----------------------------| -|version |R version 3.5.1 (2018-07-02) | -|os |macOS 10.14 | +|version |R version 3.6.0 (2019-04-26) | +|os |macOS Mojave 10.14.5 | |system |x86_64, darwin15.6.0 | |ui |RStudio | |language |(EN) | |collate |en_US.UTF-8 | |ctype |en_US.UTF-8 | -|tz |America/New_York | -|date |2019-02-11 | +|tz |America/Los_Angeles | +|date |2019-09-19 | # Dependencies -|package |old |new |Δ | -|:----------|:-----|:-----|:--| -|tibbletime |0.1.1 |0.1.2 |* | +|package |old |new |Δ | +|:----------|:-----|:----------|:--| +|tibbletime |0.1.2 |0.1.2.9000 |* | +|ellipsis |NA |0.2.0.9000 |* | +|zoo |NA |1.8-6 |* | # Revdeps -## All (3) - -|package |version |error |warning |note | -|:----------------------------------|:-------|:-----|:-------|:----| -|[anomalize](problems.md#anomalize) |0.1.1 | | |1 | -|[tidyquant](problems.md#tidyquant) |0.5.5 | |1 | | -|tsbox |0.0.3 | | | | - diff --git a/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/00check.log b/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/00check.log index 8c48a9b..b1e8fa5 100644 --- a/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/00check.log +++ b/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/00check.log @@ -1,7 +1,8 @@ * using log directory ‘/Users/davis/Desktop/r/packages/tibbletime/revdep/checks.noindex/anomalize/new/anomalize.Rcheck’ -* using R version 3.5.1 (2018-07-02) +* using R version 3.6.0 (2019-04-26) * using platform: x86_64-apple-darwin15.6.0 (64-bit) * using session charset: UTF-8 +* using options ‘--no-manual --no-build-vignettes’ * checking for file ‘anomalize/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘anomalize’ version ‘0.1.1’ @@ -58,7 +59,6 @@ * checking for unstated dependencies in vignettes ... OK * checking package vignettes in ‘inst/doc’ ... OK * checking running R code from vignettes ... NONE -* checking re-building of vignette outputs ... OK -* checking PDF version of manual ... OK +* checking re-building of vignette outputs ... SKIPPED * DONE Status: 1 NOTE diff --git a/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/00install.out b/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/00install.out index 4592bc7..83b98dd 100644 --- a/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/00install.out +++ b/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/00install.out @@ -1,5 +1,6 @@ * installing *source* package ‘anomalize’ ... ** package ‘anomalize’ successfully unpacked and MD5 sums checked +** using staged installation ** R ** data *** moving datasets to lazyload DB @@ -10,5 +11,7 @@ *** copying figures ** building package indices ** installing vignettes -** testing if installed package can be loaded +** testing if installed package can be loaded from temporary location +** testing if installed package can be loaded from final location +** testing if installed package keeps a record of temporary installation path * DONE (anomalize) diff --git a/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/Rdlatex.log b/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/Rdlatex.log deleted file mode 100644 index a879da1..0000000 --- a/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/Rdlatex.log +++ /dev/null @@ -1,391 +0,0 @@ -Hmm ... looks like a package - -This is pdfTeX, Version 3.14159265-2.6-1.40.19 (TeX Live 2018) (preloaded format=pdflatex) - restricted \write18 enabled. -entering extended mode -LaTeX2e <2018-04-01> patch level 5 -(./Rd2.tex -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/book.cls -Document Class: book 2014/09/29 v1.4h Standard LaTeX document class -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/bk10.clo)) -(/Library/Frameworks/R.framework/Resources/share/texmf/tex/latex/Rd.sty -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/ifthen.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/tools/longtable.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/tools/bm.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/alltt.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/tools/verbatim.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/url/url.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/textcomp.sty -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/ts1enc.def -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/ts1enc.dfu))) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/inconsolata/zi4.sty -`inconsolata-zi4' v1.112, 2017/01/04 Text macros for Inconsolata (msharpe) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/xkeyval/xkeyval.sty -(/Users/davis/Library/TinyTeX/texmf-dist/tex/generic/xkeyval/xkeyval.tex -(/Users/davis/Library/TinyTeX/texmf-dist/tex/generic/xkeyval/xkvutils.tex -(/Users/davis/Library/TinyTeX/texmf-dist/tex/generic/xkeyval/keyval.tex))))) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/graphics/color.sty -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/graphics-cfg/color.cfg) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/graphics-def/pdftex.def)) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/hyperref/hyperref.sty -(/Users/davis/Library/TinyTeX/texmf-dist/tex/generic/oberdiek/hobsub-hyperref.s -ty -(/Users/davis/Library/TinyTeX/texmf-dist/tex/generic/oberdiek/hobsub-generic.st -y)) (/Users/davis/Library/TinyTeX/texmf-dist/tex/generic/ifxetex/ifxetex.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/oberdiek/auxhook.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/oberdiek/kvoptions.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/hyperref/pd1enc.def) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/latexconfig/hyperref.cfg)) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/hyperref/hpdftex.def -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/oberdiek/rerunfilecheck.sty) -) - -Package hyperref Warning: Option `hyperindex' has already been used, -(hyperref) setting the option has no effect on input line 366. - - -Package hyperref Warning: Option `pagebackref' has already been used, -(hyperref) setting the option has no effect on input line 366. - -) (/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/makeidx.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/inputenc.sty) -Writing index file Rd2.idx -No file Rd2.aux. -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/ts1cmr.fd) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/hyperref/nameref.sty -(/Users/davis/Library/TinyTeX/texmf-dist/tex/generic/oberdiek/gettitlestring.st -y)) (/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/inconsolata/ot1zi4.fd) - -LaTeX Font Warning: Font shape `OML/zi4/m/n' undefined -(Font) using `OML/cmm/m/it' instead -(Font) for symbol `textless' on input line 46. - -[1{/Users/davis/Library/TinyTeX/texmf-var/fonts/map/pdftex/updmap/pdftex.map}] -Overfull \hbox (8.34766pt too wide) in paragraph at lines 106--111 -[]\OT1/cmr/m/n/10 The IQR Method uses an in-nerquar-tile range of 25 the me-dia -n. 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With the de-fault \OT1/zi4/m/n/10 alpha = 0.05\OT1/cmr/m/n/10 , - -Overfull \hbox (15.12314pt too wide) in paragraph at lines 137--138 -\OT1/cmr/m/n/10 nique for Deal-ing with Mul-ti-ple Out-liers. ASTM Stan-dard-iz -a-tion News. www.astm.org/sn[][] -[3] [4] -Overfull \hbox (37.13551pt too wide) in paragraph at lines 268--270 -[]\OT1/cmr/m/n/10 To learn more about \OT1/zi4/m/n/10 anomalize\OT1/cmr/m/n/10 -, start with the vi-gnettes: \OT1/zi4/m/n/10 browseVignettes(package = "anomali -ze") -[5] [6] [7] [8] [9] [10] [11] [12] -Overfull \hbox (5.34558pt too wide) in paragraph at lines 721--724 -\OT1/cmr/m/n/10 Twit-ter method uses \OT1/zi4/m/n/10 trend \OT1/cmr/m/n/10 to r -e-move the trend (see [][]\OT1/zi4/m/n/10 decompose[]twitter()[][][]\OT1/cmr/m/ -n/10 ). -[13] [14] -Overfull \hbox (9.2994pt too wide) in paragraph at lines 862--865 -\OT1/cmr/m/n/10 ber of ob-ser-va-tions per fre-quency (e.g. 10). See [][]\OT1/z -i4/m/n/10 tibbletime::collapse[]by()[][][] -[15] (/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/inconsolata/ts1zi4.fd) -[16] -Overfull \hbox (8.91667pt too wide) in paragraph at lines 967--969 -[]\OT1/cmr/m/n/10 A \OT1/zi4/m/n/10 tibble \OT1/cmr/m/n/10 or \OT1/zi4/m/n/10 t -bl[]time \OT1/cmr/m/n/10 ob-ject that has been pro-cessed with \OT1/zi4/m/n/10 -time[]decompose() -[17] (./Rd2.ind [18] - -LaTeX Font Warning: Font shape `OT1/zi4/m/it' undefined -(Font) using `OT1/zi4/m/n' instead on input line 14. - -[19]) (./Rd2.aux) - -LaTeX Font Warning: Some font shapes were not available, defaults substituted. - - ) -(see the transcript file for additional information)pdfTeX warning (dest): name -{Rfn.stats::stl\(\)} has been referenced but does not exist, replaced by a fixe -d one - -pdfTeX warning (dest): name{Rfn.tibbletime::collapse.Rul.by\(\)} has been refer -enced but does not exist, replaced by a fixed one - -{/Users/davis/Library/TinyTeX/texmf-dist/fonts/enc/dvips/inconsolata/i4-ts1.enc -}{/Users/davis/Library/TinyTeX/texmf-dist/fonts/enc/dvips/inconsolata/i4-ot1-0. -enc} -Output written on Rd2.pdf (19 pages, 200680 bytes). -Transcript written on Rd2.log. -Saving output to ‘anomalize-manual.pdf’ ... -Done -You may want to clean up by 'rm -Rf /var/folders/41/qx_9ygp112nfysdfgxcssgwc0000gn/T//RtmpoyoFJJ/Rd2pdfd9521e2c9f77' diff --git a/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/anomalize-Ex.Rout b/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/anomalize-Ex.Rout index d859610..05c154c 100644 --- a/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/anomalize-Ex.Rout +++ b/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/anomalize-Ex.Rout @@ -1,6 +1,6 @@ -R version 3.5.1 (2018-07-02) -- "Feather Spray" -Copyright (C) 2018 The R Foundation for Statistical Computing +R version 3.6.0 (2019-04-26) -- "Planting of a Tree" +Copyright (C) 2019 The R Foundation for Statistical Computing Platform: x86_64-apple-darwin15.6.0 (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. @@ -58,6 +58,11 @@ The following objects are masked from ‘package:base’: > tidyverse_cran_downloads %>% + time_decompose(count, method = "stl") %>% + anomalize(remainder, method = "iqr") +Warning: Detecting old grouped_df format, replacing `vars` attribute by `groups` +Warning: `cols` is now required. +Please use `cols = c(nested.col)` +Warning: `cols` is now required. +Please use `cols = c(nested.col)` # A time tibble: 6,375 x 9 # Index: date # Groups: package [15] @@ -81,7 +86,7 @@ The following objects are masked from ‘package:base’: > > cleanEx() -detaching ‘package:bindrcpp’, ‘package:dplyr’ +detaching ‘package:dplyr’ > nameEx("anomalize_methods") > ### * anomalize_methods @@ -103,123 +108,123 @@ detaching ‘package:bindrcpp’, ‘package:dplyr’ > iqr(x, alpha = 0.05, max_anoms = 0.2) [1] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" [13] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [25] "No" "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "No" - [37] "Yes" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" + [25] "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "No" "No" + [37] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" [49] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [61] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [73] "No" "No" "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" - [85] "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "Yes" "No" - [97] "No" "No" "No" "No" + [61] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "Yes" "No" + [73] "No" "Yes" "No" "No" "No" "No" "No" "No" "No" "Yes" "No" "No" + [85] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" + [97] "Yes" "No" "No" "No" > iqr(x, alpha = 0.05, max_anoms = 0.2, verbose = TRUE) $outlier [1] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" [13] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [25] "No" "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "No" - [37] "Yes" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" + [25] "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "No" "No" + [37] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" [49] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [61] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [73] "No" "No" "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" - [85] "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "Yes" "No" - [97] "No" "No" "No" "No" + [61] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "Yes" "No" + [73] "No" "Yes" "No" "No" "No" "No" "No" "No" "No" "Yes" "No" "No" + [85] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" + [97] "Yes" "No" "No" "No" $outlier_idx -[1] 37 31 90 95 80 +[1] 74 71 30 82 97 $outlier_vals -[1] 10.182908 9.908886 9.896230 9.469704 7.925595 +[1] 11.648522 10.448903 10.247076 9.950004 9.167504 $outlier_direction [1] "Up" "Up" "Up" "Up" "Up" $critical_limits limit_lower limit_upper - -4.606339 4.827444 + -4.552347 4.755455 $outlier_report # A tibble: 20 x 7 - rank index value limit_lower limit_upper outlier direction -        - 1 1 37 10.2 -4.61 4.83 Yes Up - 2 2 31 9.91 -4.61 4.83 Yes Up - 3 3 90 9.90 -4.61 4.83 Yes Up - 4 4 95 9.47 -4.61 4.83 Yes Up - 5 5 80 7.93 -4.61 4.83 Yes Up - 6 6 64 2.58 -4.61 4.83 No NA - 7 7 55 -2.27 -4.61 4.83 No NA - 8 8 96 2.45 -4.61 4.83 No NA - 9 9 20 2.31 -4.61 4.83 No NA -10 10 75 -2.06 -4.61 4.83 No NA -11 11 84 -1.93 -4.61 4.83 No NA -12 12 50 -1.88 -4.61 4.83 No NA -13 13 43 -1.78 -4.61 4.83 No NA -14 14 52 -1.74 -4.61 4.83 No NA -15 15 54 1.90 -4.61 4.83 No NA -16 16 58 1.82 -4.61 4.83 No NA -17 17 32 1.76 -4.61 4.83 No NA -18 18 89 1.73 -4.61 4.83 No NA -19 19 74 1.65 -4.61 4.83 No NA -20 20 57 -1.40 -4.61 4.83 No NA + rank index value limit_lower limit_upper outlier direction +        + 1 1 74 11.6 -4.55 4.76 Yes Up + 2 2 71 10.4 -4.55 4.76 Yes Up + 3 3 30 10.2 -4.55 4.76 Yes Up + 4 4 82 9.95 -4.55 4.76 Yes Up + 5 5 97 9.17 -4.55 4.76 Yes Up + 6 6 64 2.58 -4.55 4.76 No NA + 7 7 55 -2.27 -4.55 4.76 No NA + 8 8 96 2.45 -4.55 4.76 No NA + 9 9 20 2.31 -4.55 4.76 No NA +10 10 80 -2.07 -4.55 4.76 No NA +11 11 75 -2.06 -4.55 4.76 No NA +12 12 84 -1.93 -4.55 4.76 No NA +13 13 50 -1.88 -4.55 4.76 No NA +14 14 43 -1.78 -4.55 4.76 No NA +15 15 52 -1.74 -4.55 4.76 No NA +16 16 54 1.90 -4.55 4.76 No NA +17 17 58 1.82 -4.55 4.76 No NA +18 18 32 1.76 -4.55 4.76 No NA +19 19 89 1.73 -4.55 4.76 No NA +20 20 57 -1.40 -4.55 4.76 No NA > > gesd(x, alpha = 0.05, max_anoms = 0.2) [1] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" [13] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [25] "No" "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "No" - [37] "Yes" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" + [25] "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "No" "No" + [37] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" [49] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [61] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [73] "No" "No" "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" - [85] "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "Yes" "No" - [97] "No" "No" "No" "No" + [61] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "Yes" "No" + [73] "No" "Yes" "No" "No" "No" "No" "No" "No" "No" "Yes" "No" "No" + [85] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" + [97] "Yes" "No" "No" "No" > gesd(x, alpha = 0.05, max_anoms = 0.2, verbose = TRUE) $outlier [1] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" [13] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [25] "No" "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "No" - [37] "Yes" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" + [25] "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "No" "No" + [37] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" [49] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [61] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [73] "No" "No" "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" - [85] "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "Yes" "No" - [97] "No" "No" "No" "No" + [61] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "Yes" "No" + [73] "No" "Yes" "No" "No" "No" "No" "No" "No" "No" "Yes" "No" "No" + [85] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" + [97] "Yes" "No" "No" "No" $outlier_idx -[1] 37 31 90 95 80 +[1] 74 71 30 82 97 $outlier_vals -[1] 10.182908 9.908886 9.896230 9.469704 7.925595 +[1] 11.648522 10.448903 10.247076 9.950004 9.167504 $outlier_direction [1] "Up" "Up" "Up" "Up" "Up" $critical_limits limit_lower limit_upper - -3.441812 3.441812 + -3.31569 3.31569 $outlier_report # A tibble: 20 x 7 - rank index value limit_lower limit_upper outlier direction -        - 1 1 37 10.2 -3.45 3.45 Yes Up - 2 2 31 9.91 -3.57 3.57 Yes Up - 3 3 90 9.90 -3.55 3.55 Yes Up - 4 4 95 9.47 -3.50 3.50 Yes Up - 5 5 80 7.93 -3.55 3.55 Yes Up - 6 6 64 2.58 -3.44 3.44 No NA - 7 7 96 2.45 -3.41 3.41 No NA - 8 8 20 2.31 -3.39 3.39 No NA - 9 9 55 -2.27 -3.33 3.33 No NA -10 10 75 -2.06 -3.34 3.34 No NA -11 11 54 1.90 -3.30 3.30 No NA -12 12 84 -1.93 -3.22 3.22 No NA -13 13 58 1.82 -3.01 3.01 No NA -14 14 50 -1.88 -2.82 2.82 No NA -15 15 32 1.76 -2.74 2.74 No NA -16 16 89 1.73 -2.67 2.67 No NA -17 17 43 -1.78 -2.60 2.60 No NA -18 18 74 1.65 -2.55 2.55 No NA -19 19 52 -1.74 -2.53 2.53 No NA -20 20 92 1.43 -2.50 2.50 No NA + rank index value limit_lower limit_upper outlier direction +        + 1 1 74 11.6 -3.60 3.60 Yes Up + 2 2 71 10.4 -3.49 3.49 Yes Up + 3 3 30 10.2 -3.45 3.45 Yes Up + 4 4 82 9.95 -3.53 3.53 Yes Up + 5 5 97 9.17 -3.42 3.42 Yes Up + 6 6 64 2.58 -3.32 3.32 No NA + 7 7 96 2.45 -3.28 3.28 No NA + 8 8 20 2.31 -3.24 3.24 No NA + 9 9 55 -2.27 -3.15 3.15 No NA +10 10 80 -2.07 -3.12 3.12 No NA +11 11 75 -2.06 -3.05 3.05 No NA +12 12 54 1.90 -2.95 2.95 No NA +13 13 58 1.82 -2.78 2.78 No NA +14 14 84 -1.93 -2.57 2.57 No NA +15 15 32 1.76 -2.54 2.54 No NA +16 16 89 1.73 -2.53 2.53 No NA +17 17 50 -1.88 -2.54 2.54 No NA +18 18 43 -1.78 -2.50 2.50 No NA +19 19 52 -1.74 -2.46 2.46 No NA +20 20 92 1.43 -2.44 2.44 No NA > > @@ -318,6 +323,7 @@ The following objects are masked from ‘package:base’: + anomalize(remainder, method = "iqr") %>% + time_recompose() %>% + plot_anomalies(time_recomposed = TRUE) +Warning: Detecting old grouped_df format, replacing `vars` attribute by `groups` frequency = 7 days trend = 91 days > @@ -328,6 +334,10 @@ trend = 91 days + anomalize(remainder, method = "iqr") %>% + time_recompose() %>% + plot_anomalies(time_recomposed = TRUE, ncol = 3) +Warning: `cols` is now required. +Please use `cols = c(nested.col)` +Warning: `cols` is now required. +Please use `cols = c(nested.col)` > > > @@ -370,6 +380,7 @@ The following objects are masked from ‘package:base’: + time_decompose(count, method = "stl") %>% + anomalize(remainder, method = "iqr") %>% + plot_anomaly_decomposition() +Warning: Detecting old grouped_df format, replacing `vars` attribute by `groups` frequency = 7 days trend = 91 days > @@ -471,6 +482,9 @@ The following objects are masked from ‘package:base’: > # Basic Usage > tidyverse_cran_downloads %>% + time_apply(count, period = "1 week", .fun = mean, na.rm = TRUE) +Warning: Detecting old grouped_df format, replacing `vars` attribute by `groups` +Warning: `cols` is now required. +Please use `cols = c(nested.col)` # A time tibble: 6,375 x 4 # Index: date # Groups: package [15] @@ -525,6 +539,9 @@ The following objects are masked from ‘package:base’: > # Basic Usage > tidyverse_cran_downloads %>% + time_decompose(count, method = "stl") +Warning: Detecting old grouped_df format, replacing `vars` attribute by `groups` +Warning: `cols` is now required. +Please use `cols = c(nested.col)` # A time tibble: 6,375 x 6 # Index: date # Groups: package [15] @@ -550,6 +567,8 @@ The following objects are masked from ‘package:base’: + trend = "2 months", + merge = TRUE, + message = FALSE) +Warning: `cols` is now required. +Please use `cols = c(nested.col)` # A time tibble: 6,375 x 7 # Index: date # Groups: package [15] @@ -608,6 +627,7 @@ The following objects are masked from ‘package:base’: + filter(package == "tidyquant") %>% + ungroup() %>% + time_frequency(period = "auto") +Warning: Detecting old grouped_df format, replacing `vars` attribute by `groups` frequency = 7 days [1] 7 > @@ -679,6 +699,11 @@ The following objects are masked from ‘package:base’: + time_decompose(count, method = "stl") %>% + anomalize(remainder, method = "iqr") %>% + time_recompose() +Warning: Detecting old grouped_df format, replacing `vars` attribute by `groups` +Warning: `cols` is now required. +Please use `cols = c(nested.col)` +Warning: `cols` is now required. +Please use `cols = c(nested.col)` # A time tibble: 6,375 x 11 # Index: date # Groups: package [15] @@ -741,7 +766,7 @@ detaching ‘package:dplyr’ > cleanEx() > options(digits = 7L) > base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n") -Time elapsed: 7.176 0.111 7.296 0.001 0.001 +Time elapsed: 7.939 0.154 8.343 0.002 0.003 > grDevices::dev.off() null device 1 diff --git a/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/anomalize-Ex.pdf b/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/anomalize-Ex.pdf index 65f76a3..eee6dcd 100644 Binary files a/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/anomalize-Ex.pdf and b/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/anomalize-Ex.pdf differ diff --git a/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/anomalize-manual.log b/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/anomalize-manual.log deleted file mode 100644 index 986fa38..0000000 --- a/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/anomalize-manual.log +++ /dev/null @@ -1,572 +0,0 @@ -This is pdfTeX, Version 3.14159265-2.6-1.40.19 (TeX Live 2018) (preloaded format=pdflatex 2018.10.9) 11 FEB 2019 10:04 -entering extended mode - restricted \write18 enabled. - 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With the de-fault \OT1/zi4/m/n/10 alpha = 0.05\OT1/cmr/m/n/10 , - [] - - -Overfull \hbox (15.12314pt too wide) in paragraph at lines 137--138 -\OT1/cmr/m/n/10 nique for Deal-ing with Mul-ti-ple Out-liers. 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-{/Users/davis/Library/TinyTeX/texmf-dist/fonts/enc/dvips/inconsolata/i4-ts1.enc -}{/Users/davis/Library/TinyTeX/texmf-dist/fonts/enc/dvips/inconsolata/i4-ot1-0. -enc} -Output written on Rd2.pdf (19 pages, 200680 bytes). -PDF statistics: - 461 PDF objects out of 1000 (max. 8388607) - 421 compressed objects within 5 object streams - 148 named destinations out of 1000 (max. 500000) - 113 words of extra memory for PDF output out of 10000 (max. 10000000) - diff --git a/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/anomalize-manual.pdf b/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/anomalize-manual.pdf deleted file mode 100644 index 99c725b..0000000 Binary files a/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/anomalize-manual.pdf and /dev/null differ diff --git a/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/tests/testthat.Rout b/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/tests/testthat.Rout index 38ae2cd..def37b9 100644 --- a/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/tests/testthat.Rout +++ b/revdep/checks.noindex/anomalize/new/anomalize.Rcheck/tests/testthat.Rout @@ -1,6 +1,6 @@ -R version 3.5.1 (2018-07-02) -- "Feather Spray" -Copyright (C) 2018 The R Foundation for Statistical Computing +R version 3.6.0 (2019-04-26) -- "Planting of a Tree" +Copyright (C) 2019 The R Foundation for Statistical Computing Platform: x86_64-apple-darwin15.6.0 (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. @@ -35,15 +35,13 @@ The following objects are masked from 'package:base': > library(ggplot2) > library(tibble) -Warning message: -package 'tibble' was built under R version 3.5.2 > > # set_time_scale_template(time_scale_template()) > > test_check("anomalize") -══ testthat results ═════════════════════════════════════════════════════════════════════════════════════ -OK: 64 SKIPPED: 0 FAILED: 0 +══ testthat results ══════════════════════════════════════════════════════════════════════════════════════════════════════ +[ OK: 64 | SKIPPED: 0 | WARNINGS: 17 | FAILED: 0 ] > > proc.time() user system elapsed - 7.620 0.132 7.747 + 8.106 0.184 8.317 diff --git a/revdep/checks.noindex/anomalize/new/libraries.txt b/revdep/checks.noindex/anomalize/new/libraries.txt index 2b72691..97e189a 100644 --- a/revdep/checks.noindex/anomalize/new/libraries.txt +++ b/revdep/checks.noindex/anomalize/new/libraries.txt @@ -1,130 +1,145 @@ Library: /Users/davis/Desktop/r/packages/tibbletime/revdep/library.noindex/tibbletime/new -tibbletime (0.1.2) +ellipsis (0.2.0.9000) +tibbletime (0.1.2.9000) +zoo (1.8-6) Library: /Users/davis/Desktop/r/packages/tibbletime/revdep/library.noindex/anomalize askpass (1.1) -assertthat (0.2.0) -backports (1.1.3) +assertthat (0.2.1) +backports (1.1.4) base64enc (0.1-3) BH (1.69.0-1) -bindr (0.1.1) -bindrcpp (0.2.2) brew (1.0-6) -broom (0.5.1) -callr (3.1.1) +broom (0.5.2) +callr (3.3.1) cellranger (1.1.0) -cli (1.0.1) -clipr (0.5.0) +cli (1.1.0) +clipr (0.7.0) clisymbols (1.2.0) -colorspace (1.4-0) +colorspace (1.4-1) commonmark (1.7) -covr (3.2.1) +covr (3.3.1) crayon (1.3.4) -curl (3.3) +crosstalk (1.0.0) +curl (4.1) DBI (1.0.0) -dbplyr (1.3.0) +dbplyr (1.4.2) desc (1.2.0) -digest (0.6.18) -dplyr (0.7.8) -evaluate (0.12) +devtools (2.2.0) +digest (0.6.20) +dplyr (0.8.3) +DT (0.9) +ellipsis (0.2.0.1) +evaluate (0.14) fansi (0.4.0) -forcats (0.3.0) -forecast (8.5) +forcats (0.4.0) +forecast (8.9) fracdiff (1.4-2) -fs (1.2.6) +fs (1.3.1) generics (0.0.2) -ggplot2 (3.1.0) +ggplot2 (3.2.1) gh (1.0.1) -git2r (0.24.0) -glue (1.3.0) -gtable (0.2.0) -haven (2.0.0) -highr (0.7) -hms (0.4.2) +git2r (0.26.1) +glue (1.3.1) +gtable (0.3.0) +haven (2.1.1) +highr (0.8) +hms (0.5.1) htmltools (0.3.6) -httr (1.4.0) +htmlwidgets (1.3) +httpuv (1.5.2) +httr (1.4.1) ini (0.3.1) jsonlite (1.6) -knitr (1.21) +knitr (1.25) labeling (0.3) +later (0.8.0) lattice (0.20-38) -lazyeval (0.2.1) -lmtest (0.9-36) +lazyeval (0.2.2) +lifecycle (0.1.0) +lmtest (0.9-37) lubridate (1.7.4) magrittr (1.5) -markdown (0.9) -MASS (7.3-51.1) -Matrix (1.2-15) +markdown (1.1) +MASS (7.3-51.4) +Matrix (1.2-17) memoise (1.1.0) -mgcv (1.8-27) -mime (0.6) -modelr (0.1.3) +mgcv (1.8-28) +mime (0.7) +modelr (0.1.5) munsell (0.5.0) -nlme (3.1-137) +nlme (3.1-141) nnet (7.3-12) -openssl (1.2.1) -padr (0.4.1) -PerformanceAnalytics (1.5.2) -pillar (1.3.1) -pkgbuild (1.0.2) +openssl (1.4.1) +padr (0.5.0) +PerformanceAnalytics (1.5.3) +pillar (1.4.2) +pkgbuild (1.0.5) pkgconfig (2.0.2) pkgload (1.0.2) plogr (0.2.0) plyr (1.8.4) praise (1.0.0) prettyunits (1.0.2) -processx (3.2.1) -progress (1.2.0) +processx (3.4.1) +progress (1.2.2) +promises (1.0.1) ps (1.3.0) -purrr (0.3.0) -quadprog (1.5-5) -Quandl (2.9.1) -quantmod (0.4-13) -R6 (2.3.0) -rcmdcheck (1.3.2) +purrr (0.3.2) +quadprog (1.5-7) +Quandl (2.10.0) +quantmod (0.4-15) +R6 (2.4.0) +rcmdcheck (1.3.3) RColorBrewer (1.1-2) -Rcpp (1.0.0) -RcppArmadillo (0.9.200.7.0) +Rcpp (1.0.2) +RcppArmadillo (0.9.700.2.0) readr (1.3.1) -readxl (1.2.0) +readxl (1.3.1) rematch (1.0.1) -remotes (2.0.2) -reprex (0.2.1) +remotes (2.1.0) +reprex (0.3.0) reshape2 (1.4.3) rex (1.1.2) -rlang (0.3.1) -rmarkdown (1.11) +rlang (0.4.0) +rmarkdown (1.15) roxygen2 (6.1.1) rprojroot (1.3-2) -rstudioapi (0.9.0) -rvest (0.3.2) +rstudioapi (0.10) +rversions (2.0.0) +rvest (0.3.4) scales (1.0.0) selectr (0.4-1) sessioninfo (1.1.1) -stringi (1.2.4) +shiny (1.3.2) +sourcetools (0.1.7) +stringi (1.4.3) stringr (1.4.0) sweep (0.2.1.1) -sys (2.1) -testthat (2.0.1) -tibble (2.0.1) -tidyquant (0.5.5) -tidyr (0.8.2) +sys (3.3) +testthat (2.2.1) +tibble (2.1.3) +tidyquant (0.5.6) +tidyr (1.0.0) tidyselect (0.2.5) tidyverse (1.2.1) timeDate (3043.102) timetk (0.1.1.1) -tinytex (0.10) -tseries (0.10-46) +tinytex (0.16) +tseries (0.10-47) TTR (0.23-4) urca (1.3-0) -usethis (1.4.0) +usethis (1.5.1) utf8 (1.1.4) +vctrs (0.2.0) viridisLite (0.3.0) -whisker (0.3-2) +whisker (0.4) withr (2.1.2) -xfun (0.4) -xml2 (1.2.0) +xfun (0.9) +xml2 (1.2.2) xopen (1.0.0) +xtable (1.8-4) xts (0.11-2) yaml (2.2.0) -zoo (1.8-4) +zeallot (0.1.0) +zoo (1.8-6) diff --git a/revdep/checks.noindex/anomalize/old/anomalize.Rcheck/00check.log b/revdep/checks.noindex/anomalize/old/anomalize.Rcheck/00check.log index e43c7a7..ce062b5 100644 --- a/revdep/checks.noindex/anomalize/old/anomalize.Rcheck/00check.log +++ b/revdep/checks.noindex/anomalize/old/anomalize.Rcheck/00check.log @@ -1,7 +1,8 @@ * using log directory ‘/Users/davis/Desktop/r/packages/tibbletime/revdep/checks.noindex/anomalize/old/anomalize.Rcheck’ -* using R version 3.5.1 (2018-07-02) +* using R version 3.6.0 (2019-04-26) * using platform: x86_64-apple-darwin15.6.0 (64-bit) * using session charset: UTF-8 +* using options ‘--no-manual --no-build-vignettes’ * checking for file ‘anomalize/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘anomalize’ version ‘0.1.1’ @@ -51,14 +52,67 @@ * checking data for ASCII and uncompressed saves ... OK * checking installed files from ‘inst/doc’ ... OK * checking files in ‘vignettes’ ... OK -* checking examples ... OK +* checking examples ... ERROR +Running examples in ‘anomalize-Ex.R’ failed +The error most likely occurred in: + +> ### Name: anomalize +> ### Title: Detect anomalies using the tidyverse +> ### Aliases: anomalize +> +> ### ** Examples +> +> +> library(dplyr) + +Attaching package: ‘dplyr’ + +The following objects are masked from ‘package:stats’: + + filter, lag + +The following objects are masked from ‘package:base’: + + intersect, setdiff, setequal, union + +> +> # Needed to pass CRAN check / This is loaded by default +> set_time_scale_template(time_scale_template()) +> +> data(tidyverse_cran_downloads) +> +> tidyverse_cran_downloads %>% ++ time_decompose(count, method = "stl") %>% ++ anomalize(remainder, method = "iqr") +Warning: Detecting old grouped_df format, replacing `vars` attribute by `groups` +Warning: `cols` is now required. +Please use `cols = c(nested.col)` +Error in !.key : invalid argument type +Calls: %>% ... -> nest.grouped_df -> check_key -> is_missing +Execution halted * checking for unstated dependencies in ‘tests’ ... OK -* checking tests ... OK +* checking tests ... ERROR Running ‘testthat.R’ +Running the tests in ‘tests/testthat.R’ failed. +Last 13 lines of output: + ══ testthat results ══════════════════════════════════════════════════════════════════════════════════════════════════════ + [ OK: 33 | SKIPPED: 0 | WARNINGS: 1 | FAILED: 14 ] + 1. Error: iqr_grouped_df works (@test-anomalize.R#32) + 2. Error: gesd_grouped_df works (@test-anomalize.R#45) + 3. Error: returns a ggplot (@test-plot_anomalies.R#8) + 4. Error: grouped_tbl_time works (@test-time_apply.R#11) + 5. Error: grouped tbl_df (@test-time_decompose.R#26) + 6. Error: method = stl, auto freq/trend (@test-time_decompose.R#36) + 7. Error: method = stl, character freq/trend (@test-time_decompose.R#46) + 8. Error: method = stl, numeric freq/trend (@test-time_decompose.R#56) + 9. Error: method = twitter, auto freq/trend (@test-time_decompose.R#66) + 1. ... + + Error: testthat unit tests failed + Execution halted * checking for unstated dependencies in vignettes ... OK * checking package vignettes in ‘inst/doc’ ... OK * checking running R code from vignettes ... NONE -* checking re-building of vignette outputs ... OK -* checking PDF version of manual ... OK +* checking re-building of vignette outputs ... SKIPPED * DONE -Status: 1 NOTE +Status: 2 ERRORs, 1 NOTE diff --git a/revdep/checks.noindex/anomalize/old/anomalize.Rcheck/00install.out b/revdep/checks.noindex/anomalize/old/anomalize.Rcheck/00install.out index 4592bc7..83b98dd 100644 --- a/revdep/checks.noindex/anomalize/old/anomalize.Rcheck/00install.out +++ b/revdep/checks.noindex/anomalize/old/anomalize.Rcheck/00install.out @@ -1,5 +1,6 @@ * installing *source* package ‘anomalize’ ... ** package ‘anomalize’ successfully unpacked and MD5 sums checked +** using staged installation ** R ** data *** moving datasets to lazyload DB @@ -10,5 +11,7 @@ *** copying figures ** building package indices ** installing vignettes -** testing if installed package can be loaded +** testing if installed package can be loaded from temporary location +** testing if installed package can be loaded from final location +** testing if installed package keeps a record of temporary installation path * DONE (anomalize) diff --git a/revdep/checks.noindex/anomalize/old/anomalize.Rcheck/Rdlatex.log b/revdep/checks.noindex/anomalize/old/anomalize.Rcheck/Rdlatex.log deleted file mode 100644 index b05056e..0000000 --- a/revdep/checks.noindex/anomalize/old/anomalize.Rcheck/Rdlatex.log +++ /dev/null @@ -1,391 +0,0 @@ -Hmm ... looks like a package - -This is pdfTeX, Version 3.14159265-2.6-1.40.19 (TeX Live 2018) (preloaded format=pdflatex) - restricted \write18 enabled. -entering extended mode -LaTeX2e <2018-04-01> patch level 5 -(./Rd2.tex -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/book.cls -Document Class: book 2014/09/29 v1.4h Standard LaTeX document class -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/bk10.clo)) -(/Library/Frameworks/R.framework/Resources/share/texmf/tex/latex/Rd.sty -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/ifthen.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/tools/longtable.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/tools/bm.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/alltt.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/tools/verbatim.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/url/url.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/textcomp.sty -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/ts1enc.def -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/ts1enc.dfu))) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/inconsolata/zi4.sty -`inconsolata-zi4' v1.112, 2017/01/04 Text macros for Inconsolata (msharpe) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/xkeyval/xkeyval.sty -(/Users/davis/Library/TinyTeX/texmf-dist/tex/generic/xkeyval/xkeyval.tex -(/Users/davis/Library/TinyTeX/texmf-dist/tex/generic/xkeyval/xkvutils.tex -(/Users/davis/Library/TinyTeX/texmf-dist/tex/generic/xkeyval/keyval.tex))))) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/graphics/color.sty -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/graphics-cfg/color.cfg) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/graphics-def/pdftex.def)) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/hyperref/hyperref.sty -(/Users/davis/Library/TinyTeX/texmf-dist/tex/generic/oberdiek/hobsub-hyperref.s -ty -(/Users/davis/Library/TinyTeX/texmf-dist/tex/generic/oberdiek/hobsub-generic.st -y)) (/Users/davis/Library/TinyTeX/texmf-dist/tex/generic/ifxetex/ifxetex.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/oberdiek/auxhook.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/oberdiek/kvoptions.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/hyperref/pd1enc.def) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/latexconfig/hyperref.cfg)) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/hyperref/hpdftex.def -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/oberdiek/rerunfilecheck.sty) -) - -Package hyperref Warning: Option `hyperindex' has already been used, -(hyperref) setting the option has no effect on input line 366. - - -Package hyperref Warning: Option `pagebackref' has already been used, -(hyperref) setting the option has no effect on input line 366. - -) (/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/makeidx.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/inputenc.sty) -Writing index file Rd2.idx -No file Rd2.aux. -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/ts1cmr.fd) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/hyperref/nameref.sty -(/Users/davis/Library/TinyTeX/texmf-dist/tex/generic/oberdiek/gettitlestring.st -y)) (/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/inconsolata/ot1zi4.fd) - -LaTeX Font Warning: Font shape `OML/zi4/m/n' undefined -(Font) using `OML/cmm/m/it' instead -(Font) for symbol `textless' on input line 46. - -[1{/Users/davis/Library/TinyTeX/texmf-var/fonts/map/pdftex/updmap/pdftex.map}] -Overfull \hbox (8.34766pt too wide) in paragraph at lines 106--111 -[]\OT1/cmr/m/n/10 The IQR Method uses an in-nerquar-tile range of 25 the me-dia -n. 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-Package hyperref Warning: Option `hyperindex' has already been used, -(hyperref) setting the option has no effect on input line 366. - - -Package hyperref Warning: Option `pagebackref' has already been used, -(hyperref) setting the option has no effect on input line 366. - -) (/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/makeidx.sty) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/inputenc.sty) -Writing index file Rd2.idx -(./Rd2.aux) (/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/base/ts1cmr.fd) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/hyperref/nameref.sty -(/Users/davis/Library/TinyTeX/texmf-dist/tex/generic/oberdiek/gettitlestring.st -y)) (./Rd2.out) (./Rd2.out) -(/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/inconsolata/ot1zi4.fd) - -LaTeX Font Warning: Font shape `OML/zi4/m/n' undefined -(Font) using `OML/cmm/m/it' instead -(Font) for symbol `textless' on input line 46. - -[1{/Users/davis/Library/TinyTeX/texmf-var/fonts/map/pdftex/updmap/pdftex.map}] -(./Rd2.toc) [2] -Overfull \hbox (8.34766pt too wide) in paragraph at lines 106--111 -[]\OT1/cmr/m/n/10 The IQR Method uses an in-nerquar-tile range of 25 the me-dia -n. With the de-fault \OT1/zi4/m/n/10 alpha = 0.05\OT1/cmr/m/n/10 , - -Overfull \hbox (15.12314pt too wide) in paragraph at lines 137--138 -\OT1/cmr/m/n/10 nique for Deal-ing with Mul-ti-ple Out-liers. ASTM Stan-dard-iz -a-tion News. www.astm.org/sn[][] -[3] [4] -Overfull \hbox (37.13551pt too wide) in paragraph at lines 268--270 -[]\OT1/cmr/m/n/10 To learn more about \OT1/zi4/m/n/10 anomalize\OT1/cmr/m/n/10 -, start with the vi-gnettes: \OT1/zi4/m/n/10 browseVignettes(package = "anomali -ze") -[5] [6] [7] [8] [9] [10] [11] [12] -Overfull \hbox (5.34558pt too wide) in paragraph at lines 721--724 -\OT1/cmr/m/n/10 Twit-ter method uses \OT1/zi4/m/n/10 trend \OT1/cmr/m/n/10 to r -e-move the trend (see [][]\OT1/zi4/m/n/10 decompose[]twitter()[][][]\OT1/cmr/m/ -n/10 ). -[13] [14] -Overfull \hbox (9.2994pt too wide) in paragraph at lines 862--865 -\OT1/cmr/m/n/10 ber of ob-ser-va-tions per fre-quency (e.g. 10). See [][]\OT1/z -i4/m/n/10 tibbletime::collapse[]by()[][][] -[15] (/Users/davis/Library/TinyTeX/texmf-dist/tex/latex/inconsolata/ts1zi4.fd) -[16] -Overfull \hbox (8.91667pt too wide) in paragraph at lines 967--969 -[]\OT1/cmr/m/n/10 A \OT1/zi4/m/n/10 tibble \OT1/cmr/m/n/10 or \OT1/zi4/m/n/10 t -bl[]time \OT1/cmr/m/n/10 ob-ject that has been pro-cessed with \OT1/zi4/m/n/10 -time[]decompose() -[17] (./Rd2.ind [18] - -LaTeX Font Warning: Font shape `OT1/zi4/m/it' undefined -(Font) using `OT1/zi4/m/n' instead on input line 14. - -[19]) (./Rd2.aux) - -LaTeX Font Warning: Some font shapes were not available, defaults substituted. - - ) -(see the transcript file for additional information)pdfTeX warning (dest): name -{Rfn.stats::stl\(\)} has been referenced but does not exist, replaced by a fixe -d one - -pdfTeX warning (dest): name{Rfn.tibbletime::collapse.Rul.by\(\)} has been refer -enced but does not exist, replaced by a fixed one - -{/Users/davis/Library/TinyTeX/texmf-dist/fonts/enc/dvips/inconsolata/i4-ts1.enc -}{/Users/davis/Library/TinyTeX/texmf-dist/fonts/enc/dvips/inconsolata/i4-ot1-0. -enc} -Output written on Rd2.pdf (19 pages, 200680 bytes). -Transcript written on Rd2.log. -Saving output to ‘anomalize-manual.pdf’ ... -Done -You may want to clean up by 'rm -Rf /var/folders/41/qx_9ygp112nfysdfgxcssgwc0000gn/T//RtmpV9Pi2L/Rd2pdfd8bb3ddf7962' diff --git a/revdep/checks.noindex/anomalize/old/anomalize.Rcheck/anomalize-Ex.Rout b/revdep/checks.noindex/anomalize/old/anomalize.Rcheck/anomalize-Ex.Rout index e4a713f..33d3bdb 100644 --- a/revdep/checks.noindex/anomalize/old/anomalize.Rcheck/anomalize-Ex.Rout +++ b/revdep/checks.noindex/anomalize/old/anomalize.Rcheck/anomalize-Ex.Rout @@ -1,6 +1,6 @@ -R version 3.5.1 (2018-07-02) -- "Feather Spray" -Copyright (C) 2018 The R Foundation for Statistical Computing +R version 3.6.0 (2019-04-26) -- "Planting of a Tree" +Copyright (C) 2019 The R Foundation for Statistical Computing Platform: x86_64-apple-darwin15.6.0 (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. @@ -58,696 +58,9 @@ The following objects are masked from ‘package:base’: > tidyverse_cran_downloads %>% + time_decompose(count, method = "stl") %>% + anomalize(remainder, method = "iqr") -# A time tibble: 6,375 x 9 -# Index: date -# Groups: package [15] - package date observed season trend remainder remainder_l1 remainder_l2 -         - 1 tidyr 2017-01-01 873 -2761. 5053. -1418. -3748. 3708. - 2 tidyr 2017-01-02 1840 901. 5047. -4108. -3748. 3708. - 3 tidyr 2017-01-03 2495 1460. 5041. -4006. -3748. 3708. - 4 tidyr 2017-01-04 2906 1430. 5035. -3559. -3748. 3708. - 5 tidyr 2017-01-05 2847 1239. 5029. -3421. -3748. 3708. - 6 tidyr 2017-01-06 2756 367. 5024. -2635. -3748. 3708. - 7 tidyr 2017-01-07 1439 -2635. 5018. -944. -3748. 3708. - 8 tidyr 2017-01-08 1556 -2761. 5012. -695. -3748. 3708. - 9 tidyr 2017-01-09 3678 901. 5006. -2229. -3748. 3708. -10 tidyr 2017-01-10 7086 1460. 5000. 626. -3748. 3708. -# … with 6,365 more rows, and 1 more variable: anomaly  -> -> -> -> -> -> cleanEx() - -detaching ‘package:bindrcpp’, ‘package:dplyr’ - -> nameEx("anomalize_methods") -> ### * anomalize_methods -> -> flush(stderr()); flush(stdout()) -> -> ### Name: anomalize_methods -> ### Title: Methods that power anomalize() -> ### Aliases: anomalize_methods iqr gesd -> -> ### ** Examples -> -> -> set.seed(100) -> x <- rnorm(100) -> idx_outliers <- sample(100, size = 5) -> x[idx_outliers] <- x[idx_outliers] + 10 -> -> iqr(x, alpha = 0.05, max_anoms = 0.2) - [1] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [13] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [25] "No" "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "No" - [37] "Yes" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [49] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [61] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [73] "No" "No" "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" - [85] "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "Yes" "No" - [97] "No" "No" "No" "No" -> iqr(x, alpha = 0.05, max_anoms = 0.2, verbose = TRUE) -$outlier - [1] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [13] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [25] "No" "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "No" - [37] "Yes" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [49] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [61] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [73] "No" "No" "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" - [85] "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "Yes" "No" - [97] "No" "No" "No" "No" - -$outlier_idx -[1] 37 31 90 95 80 - -$outlier_vals -[1] 10.182908 9.908886 9.896230 9.469704 7.925595 - -$outlier_direction -[1] "Up" "Up" "Up" "Up" "Up" - -$critical_limits -limit_lower limit_upper - -4.606339 4.827444 - -$outlier_report -# A tibble: 20 x 7 - rank index value limit_lower limit_upper outlier direction -        - 1 1 37 10.2 -4.61 4.83 Yes Up - 2 2 31 9.91 -4.61 4.83 Yes Up - 3 3 90 9.90 -4.61 4.83 Yes Up - 4 4 95 9.47 -4.61 4.83 Yes Up - 5 5 80 7.93 -4.61 4.83 Yes Up - 6 6 64 2.58 -4.61 4.83 No NA - 7 7 55 -2.27 -4.61 4.83 No NA - 8 8 96 2.45 -4.61 4.83 No NA - 9 9 20 2.31 -4.61 4.83 No NA -10 10 75 -2.06 -4.61 4.83 No NA -11 11 84 -1.93 -4.61 4.83 No NA -12 12 50 -1.88 -4.61 4.83 No NA -13 13 43 -1.78 -4.61 4.83 No NA -14 14 52 -1.74 -4.61 4.83 No NA -15 15 54 1.90 -4.61 4.83 No NA -16 16 58 1.82 -4.61 4.83 No NA -17 17 32 1.76 -4.61 4.83 No NA -18 18 89 1.73 -4.61 4.83 No NA -19 19 74 1.65 -4.61 4.83 No NA -20 20 57 -1.40 -4.61 4.83 No NA - -> -> gesd(x, alpha = 0.05, max_anoms = 0.2) - [1] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [13] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [25] "No" "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "No" - [37] "Yes" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [49] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [61] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [73] "No" "No" "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" - [85] "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "Yes" "No" - [97] "No" "No" "No" "No" -> gesd(x, alpha = 0.05, max_anoms = 0.2, verbose = TRUE) -$outlier - [1] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [13] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [25] "No" "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "No" - [37] "Yes" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [49] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [61] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" - [73] "No" "No" "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" - [85] "No" "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "Yes" "No" - [97] "No" "No" "No" "No" - -$outlier_idx -[1] 37 31 90 95 80 - -$outlier_vals -[1] 10.182908 9.908886 9.896230 9.469704 7.925595 - -$outlier_direction -[1] "Up" "Up" "Up" "Up" "Up" - -$critical_limits -limit_lower limit_upper - -3.441812 3.441812 - -$outlier_report -# A tibble: 20 x 7 - rank index value limit_lower limit_upper outlier direction -        - 1 1 37 10.2 -3.45 3.45 Yes Up - 2 2 31 9.91 -3.57 3.57 Yes Up - 3 3 90 9.90 -3.55 3.55 Yes Up - 4 4 95 9.47 -3.50 3.50 Yes Up - 5 5 80 7.93 -3.55 3.55 Yes Up - 6 6 64 2.58 -3.44 3.44 No NA - 7 7 96 2.45 -3.41 3.41 No NA - 8 8 20 2.31 -3.39 3.39 No NA - 9 9 55 -2.27 -3.33 3.33 No NA -10 10 75 -2.06 -3.34 3.34 No NA -11 11 54 1.90 -3.30 3.30 No NA -12 12 84 -1.93 -3.22 3.22 No NA -13 13 58 1.82 -3.01 3.01 No NA -14 14 50 -1.88 -2.82 2.82 No NA -15 15 32 1.76 -2.74 2.74 No NA -16 16 89 1.73 -2.67 2.67 No NA -17 17 43 -1.78 -2.60 2.60 No NA -18 18 74 1.65 -2.55 2.55 No NA -19 19 52 -1.74 -2.53 2.53 No NA -20 20 92 1.43 -2.50 2.50 No NA - -> -> -> -> -> -> cleanEx() -> nameEx("decompose_methods") -> ### * decompose_methods -> -> flush(stderr()); flush(stdout()) -> -> ### Name: decompose_methods -> ### Title: Methods that power time_decompose() -> ### Aliases: decompose_methods decompose_twitter decompose_stl -> -> ### ** Examples -> -> -> library(dplyr) - -Attaching package: ‘dplyr’ - -The following objects are masked from ‘package:stats’: - - filter, lag - -The following objects are masked from ‘package:base’: - - intersect, setdiff, setequal, union - -> -> tidyverse_cran_downloads %>% -+ ungroup() %>% -+ filter(package == "tidyquant") %>% -+ decompose_stl(count) -frequency = 7 days -trend = 91 days -# A time tibble: 425 x 5 -# Index: date - date observed season trend remainder -      - 1 2017-01-01 9 -19.8 27.3 1.46 - 2 2017-01-02 55 12.4 27.4 15.2 - 3 2017-01-03 48 11.3 27.4 9.28 - 4 2017-01-04 25 8.91 27.4 -11.4 - 5 2017-01-05 22 9.80 27.5 -15.3 - 6 2017-01-06 7.00 -1.26 27.5 -19.3 - 7 2017-01-07 7 -21.3 27.5 0.807 - 8 2017-01-08 32 -19.8 27.6 24.2 - 9 2017-01-09 70 12.4 27.6 30.0 -10 2017-01-10 33 11.3 27.6 -5.95 -# … with 415 more rows -> -> -> -> -> -> cleanEx() - -detaching ‘package:dplyr’ - -> nameEx("plot_anomalies") -> ### * plot_anomalies -> -> flush(stderr()); flush(stdout()) -> -> ### Name: plot_anomalies -> ### Title: Visualize the anomalies in one or multiple time series -> ### Aliases: plot_anomalies -> -> ### ** Examples -> -> -> library(dplyr) - -Attaching package: ‘dplyr’ - -The following objects are masked from ‘package:stats’: - - filter, lag - -The following objects are masked from ‘package:base’: - - intersect, setdiff, setequal, union - -> library(ggplot2) -> -> data(tidyverse_cran_downloads) -> -> #### SINGLE TIME SERIES #### -> tidyverse_cran_downloads %>% -+ filter(package == "tidyquant") %>% -+ ungroup() %>% -+ time_decompose(count, method = "stl") %>% -+ anomalize(remainder, method = "iqr") %>% -+ time_recompose() %>% -+ plot_anomalies(time_recomposed = TRUE) -frequency = 7 days -trend = 91 days -> -> -> #### MULTIPLE TIME SERIES #### -> tidyverse_cran_downloads %>% -+ time_decompose(count, method = "stl") %>% -+ anomalize(remainder, method = "iqr") %>% -+ time_recompose() %>% -+ plot_anomalies(time_recomposed = TRUE, ncol = 3) -> -> -> -> -> cleanEx() - -detaching ‘package:ggplot2’, ‘package:dplyr’ - -> nameEx("plot_anomaly_decomposition") -> ### * plot_anomaly_decomposition -> -> flush(stderr()); flush(stdout()) -> -> ### Name: plot_anomaly_decomposition -> ### Title: Visualize the time series decomposition with anomalies shown -> ### Aliases: plot_anomaly_decomposition -> -> ### ** Examples -> -> -> library(dplyr) - -Attaching package: ‘dplyr’ - -The following objects are masked from ‘package:stats’: - - filter, lag - -The following objects are masked from ‘package:base’: - - intersect, setdiff, setequal, union - -> library(ggplot2) -> -> data(tidyverse_cran_downloads) -> -> tidyverse_cran_downloads %>% -+ filter(package == "tidyquant") %>% -+ ungroup() %>% -+ time_decompose(count, method = "stl") %>% -+ anomalize(remainder, method = "iqr") %>% -+ plot_anomaly_decomposition() -frequency = 7 days -trend = 91 days -> -> -> -> -> cleanEx() - -detaching ‘package:ggplot2’, ‘package:dplyr’ - -> nameEx("prep_tbl_time") -> ### * prep_tbl_time -> -> flush(stderr()); flush(stdout()) -> -> ### Name: prep_tbl_time -> ### Title: Automatically create tibbletime objects from tibbles -> ### Aliases: prep_tbl_time -> -> ### ** Examples -> -> -> library(dplyr) - -Attaching package: ‘dplyr’ - -The following objects are masked from ‘package:stats’: - - filter, lag - -The following objects are masked from ‘package:base’: - - intersect, setdiff, setequal, union - -> library(tibbletime) - -Attaching package: ‘tibbletime’ - -The following object is masked from ‘package:stats’: - - filter - -> -> data_tbl <- tibble( -+ date = seq.Date(from = as.Date("2018-01-01"), by = "day", length.out = 10), -+ value = rnorm(10) -+ ) -> -> prep_tbl_time(data_tbl) -# A time tibble: 10 x 2 -# Index: date - date value -   - 1 2018-01-01 -0.626 - 2 2018-01-02 0.184 - 3 2018-01-03 -0.836 - 4 2018-01-04 1.60 - 5 2018-01-05 0.330 - 6 2018-01-06 -0.820 - 7 2018-01-07 0.487 - 8 2018-01-08 0.738 - 9 2018-01-09 0.576 -10 2018-01-10 -0.305 -> -> -> -> -> cleanEx() - -detaching ‘package:tibbletime’, ‘package:dplyr’ - -> nameEx("time_apply") -> ### * time_apply -> -> flush(stderr()); flush(stdout()) -> -> ### Name: time_apply -> ### Title: Apply a function to a time series by period -> ### Aliases: time_apply -> -> ### ** Examples -> -> -> library(dplyr) - -Attaching package: ‘dplyr’ - -The following objects are masked from ‘package:stats’: - - filter, lag - -The following objects are masked from ‘package:base’: - - intersect, setdiff, setequal, union - -> -> data(tidyverse_cran_downloads) -> -> # Basic Usage -> tidyverse_cran_downloads %>% -+ time_apply(count, period = "1 week", .fun = mean, na.rm = TRUE) -# A time tibble: 6,375 x 4 -# Index: date -# Groups: package [15] - package date count time_apply -     - 1 tidyr 2017-01-01 873 2165. - 2 tidyr 2017-01-02 1840 2165. - 3 tidyr 2017-01-03 2495 2165. - 4 tidyr 2017-01-04 2906 2165. - 5 tidyr 2017-01-05 2847 2165. - 6 tidyr 2017-01-06 2756 2165. - 7 tidyr 2017-01-07 1439 2165. - 8 tidyr 2017-01-08 1556 4058. - 9 tidyr 2017-01-09 3678 4058. -10 tidyr 2017-01-10 7086 4058. -# … with 6,365 more rows -> -> -> -> -> cleanEx() - -detaching ‘package:dplyr’ - -> nameEx("time_decompose") -> ### * time_decompose -> -> flush(stderr()); flush(stdout()) -> -> ### Name: time_decompose -> ### Title: Decompose a time series in preparation for anomaly detection -> ### Aliases: time_decompose -> -> ### ** Examples -> -> -> library(dplyr) - -Attaching package: ‘dplyr’ - -The following objects are masked from ‘package:stats’: - - filter, lag - -The following objects are masked from ‘package:base’: - - intersect, setdiff, setequal, union - -> -> data(tidyverse_cran_downloads) -> -> # Basic Usage -> tidyverse_cran_downloads %>% -+ time_decompose(count, method = "stl") -# A time tibble: 6,375 x 6 -# Index: date -# Groups: package [15] - package date observed season trend remainder -       - 1 tidyr 2017-01-01 873 -2761. 5053. -1418. - 2 tidyr 2017-01-02 1840 901. 5047. -4108. - 3 tidyr 2017-01-03 2495 1460. 5041. -4006. - 4 tidyr 2017-01-04 2906 1430. 5035. -3559. - 5 tidyr 2017-01-05 2847 1239. 5029. -3421. - 6 tidyr 2017-01-06 2756 367. 5024. -2635. - 7 tidyr 2017-01-07 1439 -2635. 5018. -944. - 8 tidyr 2017-01-08 1556 -2761. 5012. -695. - 9 tidyr 2017-01-09 3678 901. 5006. -2229. -10 tidyr 2017-01-10 7086 1460. 5000. 626. -# … with 6,365 more rows -> -> # twitter -> tidyverse_cran_downloads %>% -+ time_decompose(count, -+ method = "twitter", -+ frequency = "1 week", -+ trend = "2 months", -+ merge = TRUE, -+ message = FALSE) -# A time tibble: 6,375 x 7 -# Index: date -# Groups: package [15] - package date count observed season median_spans remainder -        - 1 tidyr 2017-01-01 873 873 -2619. 5297 -1805. - 2 tidyr 2017-01-02 1840 1840 891. 5297 -4348. - 3 tidyr 2017-01-03 2495 2495 1409. 5297 -4211. - 4 tidyr 2017-01-04 2906 2906 1346. 5297 -3737. - 5 tidyr 2017-01-05 2847 2847 1199. 5297 -3649. - 6 tidyr 2017-01-06 2756 2756 247. 5297 -2788. - 7 tidyr 2017-01-07 1439 1439 -2472. 5297 -1386. - 8 tidyr 2017-01-08 1556 1556. -2619. 5297 -1122. - 9 tidyr 2017-01-09 3678 3678 891. 5297 -2510. -10 tidyr 2017-01-10 7086 7086 1409. 5297 380. -# … with 6,365 more rows -> -> -> -> -> cleanEx() - -detaching ‘package:dplyr’ - -> nameEx("time_frequency") -> ### * time_frequency -> -> flush(stderr()); flush(stdout()) -> -> ### Name: time_frequency -> ### Title: Generate a time series frequency from a periodicity -> ### Aliases: time_frequency time_trend -> -> ### ** Examples -> -> -> library(dplyr) - -Attaching package: ‘dplyr’ - -The following objects are masked from ‘package:stats’: - - filter, lag - -The following objects are masked from ‘package:base’: - - intersect, setdiff, setequal, union - -> -> data(tidyverse_cran_downloads) -> -> #### FREQUENCY DETECTION #### -> -> # period = "auto" -> tidyverse_cran_downloads %>% -+ filter(package == "tidyquant") %>% -+ ungroup() %>% -+ time_frequency(period = "auto") -frequency = 7 days -[1] 7 -> -> time_scale_template() -# A tibble: 8 x 3 - time_scale frequency trend -    -1 second 1 hour 12 hours -2 minute 1 day 14 days -3 hour 1 day 1 month -4 day 1 week 3 months -5 week 1 quarter 1 year -6 month 1 year 5 years -7 quarter 1 year 10 years -8 year 5 years 30 years -> -> # period = "1 month" -> tidyverse_cran_downloads %>% -+ filter(package == "tidyquant") %>% -+ ungroup() %>% -+ time_frequency(period = "1 month") -frequency = 31 days -[1] 31 -> -> #### TREND DETECTION #### -> -> tidyverse_cran_downloads %>% -+ filter(package == "tidyquant") %>% -+ ungroup() %>% -+ time_trend(period = "auto") -trend = 91 days -[1] 91 -> -> -> -> cleanEx() - -detaching ‘package:dplyr’ - -> nameEx("time_recompose") -> ### * time_recompose -> -> flush(stderr()); flush(stdout()) -> -> ### Name: time_recompose -> ### Title: Recompose bands separating anomalies from "normal" observations -> ### Aliases: time_recompose -> -> ### ** Examples -> -> -> library(dplyr) - -Attaching package: ‘dplyr’ - -The following objects are masked from ‘package:stats’: - - filter, lag - -The following objects are masked from ‘package:base’: - - intersect, setdiff, setequal, union - -> -> data(tidyverse_cran_downloads) -> -> # Basic Usage -> tidyverse_cran_downloads %>% -+ time_decompose(count, method = "stl") %>% -+ anomalize(remainder, method = "iqr") %>% -+ time_recompose() -# A time tibble: 6,375 x 11 -# Index: date -# Groups: package [15] - package date observed season trend remainder remainder_l1 remainder_l2 -         - 1 tidyr 2017-01-01 873 -2761. 5053. -1418. -3748. 3708. - 2 tidyr 2017-01-02 1840 901. 5047. -4108. -3748. 3708. - 3 tidyr 2017-01-03 2495 1460. 5041. -4006. -3748. 3708. - 4 tidyr 2017-01-04 2906 1430. 5035. -3559. -3748. 3708. - 5 tidyr 2017-01-05 2847 1239. 5029. -3421. -3748. 3708. - 6 tidyr 2017-01-06 2756 367. 5024. -2635. -3748. 3708. - 7 tidyr 2017-01-07 1439 -2635. 5018. -944. -3748. 3708. - 8 tidyr 2017-01-08 1556 -2761. 5012. -695. -3748. 3708. - 9 tidyr 2017-01-09 3678 901. 5006. -2229. -3748. 3708. -10 tidyr 2017-01-10 7086 1460. 5000. 626. -3748. 3708. -# … with 6,365 more rows, and 3 more variables: anomaly , -# recomposed_l1 , recomposed_l2  -> -> -> -> -> -> cleanEx() - -detaching ‘package:dplyr’ - -> nameEx("time_scale_template") -> ### * time_scale_template -> -> flush(stderr()); flush(stdout()) -> -> ### Name: set_time_scale_template -> ### Title: Get and modify time scale template -> ### Aliases: set_time_scale_template get_time_scale_template -> ### time_scale_template -> -> ### ** Examples -> -> -> get_time_scale_template() -# A tibble: 8 x 3 - time_scale frequency trend -    -1 second 1 hour 12 hours -2 minute 1 day 14 days -3 hour 1 day 1 month -4 day 1 week 3 months -5 week 1 quarter 1 year -6 month 1 year 5 years -7 quarter 1 year 10 years -8 year 5 years 30 years -> -> set_time_scale_template(time_scale_template()) -> -> -> -> -> ### *