Using Complete Function

[kellygfcengineering]

Hello! I have been trying all day to fill a data frame based on combinations of 3 variables. This is how I previously did this in R:

tidyr::complete(Date, BOM, Work_Area, fill=list(Quantity=0))

Which works swimmingly. How would I go about this using the complete function in python using datar's complete function?

[pwwang]

Is this what you wanted:

>>> from datar.all import c, f, tibble, complete
>>> 
>>> df = tibble(
...     Date=c("2020-01-01", "2020-01-02", "2020-01-03"),
...     BOM=c(1, 2, 3),
...     Work_Area=c("New York", "Arizona", "California"),
...     Quality=c(4, 5, 6),
... )
>>> 
>>> complete(df, f.Date, f.BOM, f.Work_Area, fill={"Quality": 0})
          Date     BOM   Work_Area   Quality
      <object> <int64>    <object> <float64>
0   2020-01-01       1     Arizona       0.0
1   2020-01-01       1  California       0.0
2   2020-01-01       1    New York       4.0
3   2020-01-01       2     Arizona       0.0
4   2020-01-01       2  California       0.0
5   2020-01-01       2    New York       0.0
6   2020-01-01       3     Arizona       0.0
7   2020-01-01       3  California       0.0
8   2020-01-01       3    New York       0.0
9   2020-01-02       1     Arizona       0.0
10  2020-01-02       1  California       0.0
11  2020-01-02       1    New York       0.0
12  2020-01-02       2     Arizona       5.0
13  2020-01-02       2  California       0.0
14  2020-01-02       2    New York       0.0
15  2020-01-02       3     Arizona       0.0
16  2020-01-02       3  California       0.0
17  2020-01-02       3    New York       0.0
18  2020-01-03       1     Arizona       0.0
19  2020-01-03       1  California       0.0
20  2020-01-03       1    New York       0.0
21  2020-01-03       2     Arizona       0.0
22  2020-01-03       2  California       0.0
23  2020-01-03       2    New York       0.0
24  2020-01-03       3     Arizona       0.0
25  2020-01-03       3  California       6.0
26  2020-01-03       3    New York       0.0

With R:

r$> library(dplyr)  
r$> library(tidyr) 
r$> df = tibble( 
        Date=c("2020-01-01", "2020-01-02", "2020-01-03"), 
        BOM=c(1, 2, 3), 
        Work_Area=c("New York", "Arizona", "California"), 
        Quality=c(4, 5, 6), 
    )          
r$> out = complete(df, Date, BOM, Work_Area, fill=list(Quality=0))                                   
r$> print(out, n=27)                                                                                 
# A tibble: 27 × 4
   Date         BOM Work_Area  Quality
   <chr>      <dbl> <chr>        <dbl>
 1 2020-01-01     1 Arizona          0
 2 2020-01-01     1 California       0
 3 2020-01-01     1 New York         4
 4 2020-01-01     2 Arizona          0
 5 2020-01-01     2 California       0
 6 2020-01-01     2 New York         0
 7 2020-01-01     3 Arizona          0
 8 2020-01-01     3 California       0
 9 2020-01-01     3 New York         0
10 2020-01-02     1 Arizona          0
11 2020-01-02     1 California       0
12 2020-01-02     1 New York         0
13 2020-01-02     2 Arizona          5
14 2020-01-02     2 California       0
15 2020-01-02     2 New York         0
16 2020-01-02     3 Arizona          0
17 2020-01-02     3 California       0
18 2020-01-02     3 New York         0
19 2020-01-03     1 Arizona          0
20 2020-01-03     1 California       0
21 2020-01-03     1 New York         0
22 2020-01-03     2 Arizona          0
23 2020-01-03     2 California       0
24 2020-01-03     2 New York         0
25 2020-01-03     3 Arizona          0
26 2020-01-03     3 California       6
27 2020-01-03     3 New York         0                 

[kellygfcengineering]

Ahhh, yes! thank you!!