From 1335010b52f6147b3810aa8ab2ceb90559cbb963 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Bogumi=C5=82=20Kami=C5=84ski?= <bkamins@sgh.waw.pl>
Date: Wed, 25 Jul 2018 11:21:10 +0200
Subject: [PATCH] update to DataFrames 0.11.7

---
 01_constructors.ipynb  | 184 ++++++++++++++++++++++-----------------
 02_basicinfo.ipynb     | 171 +++++++++++++++----------------------
 03_missingvalues.ipynb |  64 ++++++++------
 04_loadsave.ipynb      |  31 +++----
 05_columns.ipynb       | 190 +++++++++++++++++++++++------------------
 08_joins.ipynb         |  58 +++++++++----
 10_transforms.ipynb    |   2 +-
 README.md              |  13 ++-
 8 files changed, 378 insertions(+), 335 deletions(-)

diff --git a/01_constructors.ipynb b/01_constructors.ipynb
index baecd5a..70a5726 100644
--- a/01_constructors.ipynb
+++ b/01_constructors.ipynb
@@ -5,7 +5,7 @@
    "metadata": {},
    "source": [
     "# Introduction to DataFrames\n",
-    "**[Bogumił Kamiński](http://bogumilkaminski.pl/about/), May 23, 2018**\n",
+    "**[Bogumił Kamiński](http://bogumilkaminski.pl/about/), July 25, 2018**\n",
     "\n",
     "Let's get started by loading the `DataFrames` package."
    ]
@@ -13,9 +13,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "using DataFrames"
@@ -77,15 +75,15 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>A</th><th>B</th><th>C</th></tr></thead><tbody><tr><th>1</th><td>1</td><td>0.865057</td><td>Jds</td></tr><tr><th>2</th><td>2</td><td>0.870442</td><td>hDG</td></tr><tr><th>3</th><td>3</td><td>0.128666</td><td>oyt</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>A</th><th>B</th><th>C</th></tr></thead><tbody><tr><th>1</th><td>1</td><td>0.582939</td><td>eDh</td></tr><tr><th>2</th><td>2</td><td>0.899657</td><td>Uma</td></tr><tr><th>3</th><td>3</td><td>0.873748</td><td>RnO</td></tr></tbody></table>"
       ],
       "text/plain": [
        "3×3 DataFrames.DataFrame\n",
        "│ Row │ A │ B        │ C   │\n",
        "├─────┼───┼──────────┼─────┤\n",
-       "│ 1   │ 1 │ 0.865057 │ Jds │\n",
-       "│ 2   │ 2 │ 0.870442 │ hDG │\n",
-       "│ 3   │ 3 │ 0.128666 │ oyt │"
+       "│ 1   │ 1 │ 0.582939 │ eDh │\n",
+       "│ 2   │ 2 │ 0.899657 │ Uma │\n",
+       "│ 3   │ 3 │ 0.873748 │ RnO │"
       ]
      },
      "execution_count": 3,
@@ -183,15 +181,15 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>x1</th><th>x2</th><th>x3</th></tr></thead><tbody><tr><th>1</th><td>0.738969</td><td>0.476396</td><td>0.926968</td></tr><tr><th>2</th><td>0.498559</td><td>0.190063</td><td>0.839678</td></tr><tr><th>3</th><td>0.0957712</td><td>0.843156</td><td>0.120698</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>x1</th><th>x2</th><th>x3</th></tr></thead><tbody><tr><th>1</th><td>0.291477</td><td>0.589915</td><td>0.321527</td></tr><tr><th>2</th><td>0.230679</td><td>0.0387716</td><td>0.539359</td></tr><tr><th>3</th><td>0.481537</td><td>0.494867</td><td>0.649062</td></tr></tbody></table>"
       ],
       "text/plain": [
        "3×3 DataFrames.DataFrame\n",
-       "│ Row │ x1        │ x2       │ x3       │\n",
-       "├─────┼───────────┼──────────┼──────────┤\n",
-       "│ 1   │ 0.738969  │ 0.476396 │ 0.926968 │\n",
-       "│ 2   │ 0.498559  │ 0.190063 │ 0.839678 │\n",
-       "│ 3   │ 0.0957712 │ 0.843156 │ 0.120698 │"
+       "│ Row │ x1       │ x2        │ x3       │\n",
+       "├─────┼──────────┼───────────┼──────────┤\n",
+       "│ 1   │ 0.291477 │ 0.589915  │ 0.321527 │\n",
+       "│ 2   │ 0.230679 │ 0.0387716 │ 0.539359 │\n",
+       "│ 3   │ 0.481537 │ 0.494867  │ 0.649062 │"
       ]
      },
      "execution_count": 6,
@@ -222,11 +220,11 @@
       "\u001b[1m\u001b[33mWARNING: \u001b[39m\u001b[22m\u001b[33mpassing columns argument with non-AbstractVector entries is deprecated\u001b[39m\n",
       "Stacktrace:\n",
       " [1] \u001b[1mdepwarn\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::String, ::Symbol\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\deprecated.jl:70\u001b[22m\u001b[22m\n",
-      " [2] \u001b[1m#DataFrame#57\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Bool, ::Type{T} where T, ::Array{Float64,1}, ::Array{Symbol,1}\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\dataframe\\dataframe.jl:154\u001b[22m\u001b[22m\n",
+      " [2] \u001b[1m#DataFrame#62\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Bool, ::Type{T} where T, ::Array{Float64,1}, ::Array{Symbol,1}\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\dataframe\\dataframe.jl:154\u001b[22m\u001b[22m\n",
       " [3] \u001b[1mDataFrames.DataFrame\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Array{Float64,1}\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\dataframe\\dataframe.jl:152\u001b[22m\u001b[22m\n",
       " [4] \u001b[1minclude_string\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::String, ::String\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\loading.jl:522\u001b[22m\u001b[22m\n",
       " [5] \u001b[1mexecute_request\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::ZMQ.Socket, ::IJulia.Msg\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\IJulia\\src\\execute_request.jl:158\u001b[22m\u001b[22m\n",
-      " [6] \u001b[1m(::Compat.#inner#17{Array{Any,1},IJulia.#execute_request,Tuple{ZMQ.Socket,IJulia.Msg}})\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\Compat\\src\\Compat.jl:385\u001b[22m\u001b[22m\n",
+      " [6] \u001b[1m(::Compat.#inner#14{Array{Any,1},IJulia.#execute_request,Tuple{ZMQ.Socket,IJulia.Msg}})\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\Compat\\src\\Compat.jl:332\u001b[22m\u001b[22m\n",
       " [7] \u001b[1meventloop\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::ZMQ.Socket\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\IJulia\\src\\eventloop.jl:8\u001b[22m\u001b[22m\n",
       " [8] \u001b[1m(::IJulia.##14#17)\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\task.jl:335\u001b[22m\u001b[22m\n",
       "while loading In[7], in expression starting on line 1\n"
@@ -235,13 +233,13 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>x1</th><th>x2</th><th>x3</th></tr></thead><tbody><tr><th>1</th><td>0.613673</td><td>0.9388</td><td>0.976714</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>x1</th><th>x2</th><th>x3</th></tr></thead><tbody><tr><th>1</th><td>0.694614</td><td>0.305183</td><td>0.375302</td></tr></tbody></table>"
       ],
       "text/plain": [
        "1×3 DataFrames.DataFrame\n",
-       "│ Row │ x1       │ x2     │ x3       │\n",
-       "├─────┼──────────┼────────┼──────────┤\n",
-       "│ 1   │ 0.613673 │ 0.9388 │ 0.976714 │"
+       "│ Row │ x1       │ x2       │ x3       │\n",
+       "├─────┼──────────┼──────────┼──────────┤\n",
+       "│ 1   │ 0.694614 │ 0.305183 │ 0.375302 │"
       ]
      },
      "execution_count": 7,
@@ -283,7 +281,7 @@
     }
    ],
    "source": [
-    "DataFrame(transpose([1, 2, 3]))"
+    "DataFrame(transpose([1, 2, 3])) # permutedims in Julia 0.7"
    ]
   },
   {
@@ -336,15 +334,15 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>x1</th><th>x2</th><th>x3</th><th>x4</th></tr></thead><tbody><tr><th>1</th><td>0.874557</td><td>0.777246</td><td>0.949467</td><td>0.697868</td></tr><tr><th>2</th><td>0.579164</td><td>0.816029</td><td>0.191466</td><td>0.0563065</td></tr><tr><th>3</th><td>0.280777</td><td>0.795716</td><td>0.201309</td><td>0.191633</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>x1</th><th>x2</th><th>x3</th><th>x4</th></tr></thead><tbody><tr><th>1</th><td>0.957768</td><td>0.222008</td><td>0.569215</td><td>0.553819</td></tr><tr><th>2</th><td>0.0885923</td><td>0.49824</td><td>0.61231</td><td>0.985774</td></tr><tr><th>3</th><td>0.152064</td><td>0.804575</td><td>0.825947</td><td>0.653275</td></tr></tbody></table>"
       ],
       "text/plain": [
        "3×4 DataFrames.DataFrame\n",
-       "│ Row │ x1       │ x2       │ x3       │ x4        │\n",
-       "├─────┼──────────┼──────────┼──────────┼───────────┤\n",
-       "│ 1   │ 0.874557 │ 0.777246 │ 0.949467 │ 0.697868  │\n",
-       "│ 2   │ 0.579164 │ 0.816029 │ 0.191466 │ 0.0563065 │\n",
-       "│ 3   │ 0.280777 │ 0.795716 │ 0.201309 │ 0.191633  │"
+       "│ Row │ x1        │ x2       │ x3       │ x4       │\n",
+       "├─────┼───────────┼──────────┼──────────┼──────────┤\n",
+       "│ 1   │ 0.957768  │ 0.222008 │ 0.569215 │ 0.553819 │\n",
+       "│ 2   │ 0.0885923 │ 0.49824  │ 0.61231  │ 0.985774 │\n",
+       "│ 3   │ 0.152064  │ 0.804575 │ 0.825947 │ 0.653275 │"
       ]
      },
      "execution_count": 10,
@@ -371,15 +369,15 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>a</th><th>b</th><th>c</th><th>d</th></tr></thead><tbody><tr><th>1</th><td>0.627336</td><td>0.850384</td><td>0.225164</td><td>0.617465</td></tr><tr><th>2</th><td>0.645045</td><td>0.709581</td><td>0.0780468</td><td>0.0941601</td></tr><tr><th>3</th><td>0.48563</td><td>0.608378</td><td>0.777213</td><td>0.630866</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>a</th><th>b</th><th>c</th><th>d</th></tr></thead><tbody><tr><th>1</th><td>0.188787</td><td>0.903936</td><td>0.500736</td><td>0.811463</td></tr><tr><th>2</th><td>0.341302</td><td>0.557099</td><td>0.41954</td><td>0.382749</td></tr><tr><th>3</th><td>0.0751378</td><td>0.430165</td><td>0.293501</td><td>0.253147</td></tr></tbody></table>"
       ],
       "text/plain": [
        "3×4 DataFrames.DataFrame\n",
-       "│ Row │ a        │ b        │ c         │ d         │\n",
-       "├─────┼──────────┼──────────┼───────────┼───────────┤\n",
-       "│ 1   │ 0.627336 │ 0.850384 │ 0.225164  │ 0.617465  │\n",
-       "│ 2   │ 0.645045 │ 0.709581 │ 0.0780468 │ 0.0941601 │\n",
-       "│ 3   │ 0.48563  │ 0.608378 │ 0.777213  │ 0.630866  │"
+       "│ Row │ a         │ b        │ c        │ d        │\n",
+       "├─────┼───────────┼──────────┼──────────┼──────────┤\n",
+       "│ 1   │ 0.188787  │ 0.903936 │ 0.500736 │ 0.811463 │\n",
+       "│ 2   │ 0.341302  │ 0.557099 │ 0.41954  │ 0.382749 │\n",
+       "│ 3   │ 0.0751378 │ 0.430165 │ 0.293501 │ 0.253147 │"
       ]
      },
      "execution_count": 11,
@@ -408,13 +406,13 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>A</th><th>B</th><th>C</th></tr></thead><tbody><tr><th>1</th><td>147259888</td><td>1.08013e-319</td><td>missing</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>A</th><th>B</th><th>C</th></tr></thead><tbody><tr><th>1</th><td>0</td><td>0.0</td><td>missing</td></tr></tbody></table>"
       ],
       "text/plain": [
        "1×3 DataFrames.DataFrame\n",
-       "│ Row │ A         │ B            │ C       │\n",
-       "├─────┼───────────┼──────────────┼─────────┤\n",
-       "│ 1   │ 147259888 │ 1.08013e-319 │ \u001b[90mmissing\u001b[39m │"
+       "│ Row │ A │ B   │ C       │\n",
+       "├─────┼───┼─────┼─────────┤\n",
+       "│ 1   │ 0 │ 0.0 │ \u001b[90mmissing\u001b[39m │"
       ]
      },
      "execution_count": 12,
@@ -430,9 +428,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Here we create a `DataFrame`, but column `:C` is #undef and Jupyter has problem with displaying it. (This works OK at the REPL.)\n",
-    "\n",
-    "This will be fixed in next release of DataFrames!"
+    "Here we create a `DataFrame` where `:C` is #undef"
    ]
   },
   {
@@ -441,24 +437,20 @@
    "metadata": {},
    "outputs": [
     {
-     "ename": "UndefRefError",
-     "evalue": "\u001b[91mUndefRefError: access to undefined reference\u001b[39m",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[91mUndefRefError: access to undefined reference\u001b[39m",
-      "",
-      "Stacktrace:",
-      " [1] \u001b[1mgetindex\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Array{String,1}, ::Int64\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\array.jl:554\u001b[22m\u001b[22m",
-      " [2] \u001b[1mgetindex\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::DataFrames.DataFrame, ::Int64, ::Symbol\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\dataframe\\dataframe.jl:275\u001b[22m\u001b[22m",
-      " [3] \u001b[1mshow\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::IOContext{Base.AbstractIOBuffer{Array{UInt8,1}}}, ::MIME{Symbol(\"text/html\")}, ::DataFrames.DataFrame\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\abstractdataframe\\io.jl:110\u001b[22m\u001b[22m",
-      " [4] \u001b[1mlimitstringmime\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::MIME{Symbol(\"text/html\")}, ::DataFrames.DataFrame\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\IJulia\\src\\inline.jl:24\u001b[22m\u001b[22m",
-      " [5] \u001b[1mdisplay_dict\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::DataFrames.DataFrame\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\IJulia\\src\\execute_request.jl:43\u001b[22m\u001b[22m",
-      " [6] \u001b[1m(::Compat.#inner#17{Array{Any,1},IJulia.#display_dict,Tuple{DataFrames.DataFrame}})\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\Compat\\src\\Compat.jl:385\u001b[22m\u001b[22m",
-      " [7] \u001b[1mexecute_request\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::ZMQ.Socket, ::IJulia.Msg\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\IJulia\\src\\execute_request.jl:186\u001b[22m\u001b[22m",
-      " [8] \u001b[1m(::Compat.#inner#17{Array{Any,1},IJulia.#execute_request,Tuple{ZMQ.Socket,IJulia.Msg}})\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\Compat\\src\\Compat.jl:385\u001b[22m\u001b[22m",
-      " [9] \u001b[1meventloop\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::ZMQ.Socket\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\IJulia\\src\\eventloop.jl:8\u001b[22m\u001b[22m",
-      " [10] \u001b[1m(::IJulia.##14#17)\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\task.jl:335\u001b[22m\u001b[22m"
-     ]
+     "data": {
+      "text/html": [
+       "<table class=\"data-frame\"><thead><tr><th></th><th>A</th><th>B</th><th>C</th></tr></thead><tbody><tr><th>1</th><td>-1</td><td>2.03553e-315</td><td>#undef</td></tr></tbody></table>"
+      ],
+      "text/plain": [
+       "1×3 DataFrames.DataFrame\n",
+       "│ Row │ A  │ B            │ C      │\n",
+       "├─────┼────┼──────────────┼────────┤\n",
+       "│ 1   │ -1 │ 2.03553e-315 │ #undef │"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -510,15 +502,15 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>x1</th><th>x2</th><th>x3</th><th>x4</th><th>x5</th></tr></thead><tbody><tr><th>1</th><td>202568848</td><td>199866128</td><td>1649267441664</td><td>0</td><td>439701264</td></tr><tr><th>2</th><td>147292368</td><td>147292368</td><td>0</td><td>0</td><td>148642768</td></tr><tr><th>3</th><td>147293072</td><td>147292432</td><td>0</td><td>0</td><td>439701424</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>x1</th><th>x2</th><th>x3</th><th>x4</th><th>x5</th></tr></thead><tbody><tr><th>1</th><td>166116144</td><td>165712048</td><td>166110096</td><td>169519056</td><td>165712048</td></tr><tr><th>2</th><td>164408368</td><td>167317968</td><td>111313296</td><td>111313680</td><td>164408368</td></tr><tr><th>3</th><td>111313296</td><td>141233040</td><td>141233200</td><td>141238528</td><td>141233232</td></tr></tbody></table>"
       ],
       "text/plain": [
        "3×5 DataFrames.DataFrame\n",
-       "│ Row │ x1        │ x2        │ x3            │ x4 │ x5        │\n",
-       "├─────┼───────────┼───────────┼───────────────┼────┼───────────┤\n",
-       "│ 1   │ 202568848 │ 199866128 │ 1649267441664 │ 0  │ 439701264 │\n",
-       "│ 2   │ 147292368 │ 147292368 │ 0             │ 0  │ 148642768 │\n",
-       "│ 3   │ 147293072 │ 147292432 │ 0             │ 0  │ 439701424 │"
+       "│ Row │ x1        │ x2        │ x3        │ x4        │ x5        │\n",
+       "├─────┼───────────┼───────────┼───────────┼───────────┼───────────┤\n",
+       "│ 1   │ 166116144 │ 165712048 │ 166110096 │ 169519056 │ 165712048 │\n",
+       "│ 2   │ 164408368 │ 167317968 │ 111313296 │ 111313680 │ 164408368 │\n",
+       "│ 3   │ 111313296 │ 141233040 │ 141233200 │ 141238528 │ 141233232 │"
       ]
      },
      "execution_count": 15,
@@ -545,16 +537,16 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>x1</th><th>x2</th></tr></thead><tbody><tr><th>1</th><td>148644688</td><td>2.17246e-315</td></tr><tr><th>2</th><td>147261328</td><td>2.17242e-315</td></tr><tr><th>3</th><td>147261328</td><td>2.17246e-315</td></tr><tr><th>4</th><td>0</td><td>2.20078e-315</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>x1</th><th>x2</th></tr></thead><tbody><tr><th>1</th><td>166692528</td><td>8.26715e-316</td></tr><tr><th>2</th><td>141234768</td><td>2.11841e-315</td></tr><tr><th>3</th><td>111411280</td><td>6.97793e-316</td></tr><tr><th>4</th><td>144117920</td><td>0.0</td></tr></tbody></table>"
       ],
       "text/plain": [
        "4×2 DataFrames.DataFrame\n",
        "│ Row │ x1        │ x2           │\n",
        "├─────┼───────────┼──────────────┤\n",
-       "│ 1   │ 148644688 │ 2.17246e-315 │\n",
-       "│ 2   │ 147261328 │ 2.17242e-315 │\n",
-       "│ 3   │ 147261328 │ 2.17246e-315 │\n",
-       "│ 4   │ 0         │ 2.20078e-315 │"
+       "│ 1   │ 166692528 │ 8.26715e-316 │\n",
+       "│ 2   │ 141234768 │ 2.11841e-315 │\n",
+       "│ 3   │ 111411280 │ 6.97793e-316 │\n",
+       "│ 4   │ 144117920 │ 0.0          │"
       ]
      },
      "execution_count": 16,
@@ -850,7 +842,7 @@
       "\u001b[91mcannot convert a DataFrame containing missing values to array (found for column y)\u001b[39m",
       "",
       "Stacktrace:",
-      " [1] \u001b[1mconvert\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Type{Array{Int64,2}}, ::DataFrames.DataFrame\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\abstractdataframe\\abstractdataframe.jl:626\u001b[22m\u001b[22m",
+      " [1] \u001b[1mconvert\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Type{Array{Int64,2}}, ::DataFrames.DataFrame\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\abstractdataframe\\abstractdataframe.jl:716\u001b[22m\u001b[22m",
       " [2] \u001b[1mArray{Int64,2}\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::DataFrames.DataFrame\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\sysimg.jl:77\u001b[22m\u001b[22m"
      ]
     }
@@ -913,15 +905,15 @@
       "\u001b[1m\u001b[33mWARNING: \u001b[39m\u001b[22m\u001b[33mDuplicate variable names are deprecated: pass makeunique=true to add a suffix automatically.\u001b[39m\n",
       "Stacktrace:\n",
       " [1] \u001b[1mdepwarn\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::String, ::Symbol\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\deprecated.jl:70\u001b[22m\u001b[22m\n",
-      " [2] \u001b[1m#make_unique#3\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Bool, ::Function, ::Array{Symbol,1}\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\other\\utils.jl:61\u001b[22m\u001b[22m\n",
+      " [2] \u001b[1m#make_unique#3\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Bool, ::Function, ::Array{Symbol,1}\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\other\\utils.jl:64\u001b[22m\u001b[22m\n",
       " [3] \u001b[1m(::DataFrames.#kw##make_unique)\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Array{Any,1}, ::DataFrames.#make_unique, ::Array{Symbol,1}\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\<missing>:0\u001b[22m\u001b[22m\n",
       " [4] \u001b[1m#Index#6\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\other\\index.jl:12\u001b[22m\u001b[22m [inlined]\n",
       " [5] \u001b[1m(::Core.#kw#Type)\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Array{Any,1}, ::Type{DataFrames.Index}, ::Array{Symbol,1}\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\<missing>:0\u001b[22m\u001b[22m\n",
-      " [6] \u001b[1m#DataFrame#47\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Bool, ::Type{T} where T, ::Pair{Symbol,Int64}, ::Vararg{Pair{Symbol,Int64},N} where N\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\dataframe\\dataframe.jl:126\u001b[22m\u001b[22m\n",
+      " [6] \u001b[1m#DataFrame#52\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Bool, ::Type{T} where T, ::Pair{Symbol,Int64}, ::Vararg{Pair{Symbol,Int64},N} where N\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\dataframe\\dataframe.jl:126\u001b[22m\u001b[22m\n",
       " [7] \u001b[1mDataFrames.DataFrame\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Pair{Symbol,Int64}, ::Pair{Symbol,Int64}, ::Pair{Symbol,Int64}\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\dataframe\\dataframe.jl:124\u001b[22m\u001b[22m\n",
       " [8] \u001b[1minclude_string\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::String, ::String\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\loading.jl:522\u001b[22m\u001b[22m\n",
       " [9] \u001b[1mexecute_request\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::ZMQ.Socket, ::IJulia.Msg\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\IJulia\\src\\execute_request.jl:158\u001b[22m\u001b[22m\n",
-      " [10] \u001b[1m(::Compat.#inner#17{Array{Any,1},IJulia.#execute_request,Tuple{ZMQ.Socket,IJulia.Msg}})\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\Compat\\src\\Compat.jl:385\u001b[22m\u001b[22m\n",
+      " [10] \u001b[1m(::Compat.#inner#14{Array{Any,1},IJulia.#execute_request,Tuple{ZMQ.Socket,IJulia.Msg}})\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\Compat\\src\\Compat.jl:332\u001b[22m\u001b[22m\n",
       " [11] \u001b[1meventloop\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::ZMQ.Socket\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\IJulia\\src\\eventloop.jl:8\u001b[22m\u001b[22m\n",
       " [12] \u001b[1m(::IJulia.##14#17)\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\task.jl:335\u001b[22m\u001b[22m\n",
       "while loading In[28], in expression starting on line 1\n"
@@ -968,17 +960,17 @@
       "\u001b[1m\u001b[33mWARNING: \u001b[39m\u001b[22m\u001b[33mDuplicate variable names are deprecated: pass makeunique=true to add a suffix automatically.\u001b[39m\n",
       "Stacktrace:\n",
       " [1] \u001b[1mdepwarn\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::String, ::Symbol\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\deprecated.jl:70\u001b[22m\u001b[22m\n",
-      " [2] \u001b[1m#make_unique#3\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Bool, ::Function, ::Array{Symbol,1}\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\other\\utils.jl:61\u001b[22m\u001b[22m\n",
+      " [2] \u001b[1m#make_unique#3\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Bool, ::Function, ::Array{Symbol,1}\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\other\\utils.jl:64\u001b[22m\u001b[22m\n",
       " [3] \u001b[1m(::DataFrames.#kw##make_unique)\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Array{Any,1}, ::DataFrames.#make_unique, ::Array{Symbol,1}\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\<missing>:0\u001b[22m\u001b[22m\n",
       " [4] \u001b[1m#Index#6\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\other\\index.jl:12\u001b[22m\u001b[22m [inlined]\n",
       " [5] \u001b[1m(::Core.#kw#Type)\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Array{Any,1}, ::Type{DataFrames.Index}, ::Array{Symbol,1}\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\<missing>:0\u001b[22m\u001b[22m\n",
-      " [6] \u001b[1m#DataFrame#47\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Bool, ::Type{T} where T, ::Pair{Symbol,Int64}, ::Vararg{Pair{Symbol,#s8} where #s8,N} where N\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\dataframe\\dataframe.jl:126\u001b[22m\u001b[22m\n",
+      " [6] \u001b[1m#DataFrame#52\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Bool, ::Type{T} where T, ::Pair{Symbol,Int64}, ::Vararg{Pair{Symbol,#s8} where #s8,N} where N\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\dataframe\\dataframe.jl:126\u001b[22m\u001b[22m\n",
       " [7] \u001b[1mDataFrames.DataFrame\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Pair{Symbol,Int64}, ::Pair{Symbol,Int64}, ::Pair{Symbol,Bool}\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\dataframe\\dataframe.jl:124\u001b[22m\u001b[22m\n",
-      " [8] \u001b[1m#DataFrame#56\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\dataframe\\dataframe.jl:145\u001b[22m\u001b[22m [inlined]\n",
+      " [8] \u001b[1m#DataFrame#61\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\dataframe\\dataframe.jl:145\u001b[22m\u001b[22m [inlined]\n",
       " [9] \u001b[1m(::Core.#kw#Type)\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Array{Any,1}, ::Type{DataFrames.DataFrame}\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\<missing>:0\u001b[22m\u001b[22m\n",
       " [10] \u001b[1minclude_string\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::String, ::String\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\loading.jl:522\u001b[22m\u001b[22m\n",
       " [11] \u001b[1mexecute_request\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::ZMQ.Socket, ::IJulia.Msg\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\IJulia\\src\\execute_request.jl:158\u001b[22m\u001b[22m\n",
-      " [12] \u001b[1m(::Compat.#inner#17{Array{Any,1},IJulia.#execute_request,Tuple{ZMQ.Socket,IJulia.Msg}})\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\Compat\\src\\Compat.jl:385\u001b[22m\u001b[22m\n",
+      " [12] \u001b[1m(::Compat.#inner#14{Array{Any,1},IJulia.#execute_request,Tuple{ZMQ.Socket,IJulia.Msg}})\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\Compat\\src\\Compat.jl:332\u001b[22m\u001b[22m\n",
       " [13] \u001b[1meventloop\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::ZMQ.Socket\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\IJulia\\src\\eventloop.jl:8\u001b[22m\u001b[22m\n",
       " [14] \u001b[1m(::IJulia.##14#17)\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\task.jl:335\u001b[22m\u001b[22m\n",
       "while loading In[29], in expression starting on line 1\n"
@@ -1004,11 +996,45 @@
    "source": [
     "df = DataFrame(a=1, a=2, makeunique=true)"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finallly observe that `nothing` is not printed when displaying a `DataFrame`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<table class=\"data-frame\"><thead><tr><th></th><th>x</th><th>y</th></tr></thead><tbody><tr><th>1</th><td>1</td><td></td></tr><tr><th>2</th><td></td><td>a</td></tr></tbody></table>"
+      ],
+      "text/plain": [
+       "2×2 DataFrames.DataFrame\n",
+       "│ Row │ x │ y │\n",
+       "├─────┼───┼───┤\n",
+       "│ 1   │ 1 │   │\n",
+       "│ 2   │   │ a │"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "DataFrame(x=[1, nothing], y=[nothing, \"a\"])"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Julia 0.6.0",
+   "display_name": "Julia 0.6.2",
    "language": "julia",
    "name": "julia-0.6"
   },
@@ -1016,7 +1042,7 @@
    "file_extension": ".jl",
    "mimetype": "application/julia",
    "name": "julia",
-   "version": "0.6.0"
+   "version": "0.6.3"
   }
  },
  "nbformat": 4,
diff --git a/02_basicinfo.ipynb b/02_basicinfo.ipynb
index d4107a5..a34cece 100644
--- a/02_basicinfo.ipynb
+++ b/02_basicinfo.ipynb
@@ -5,15 +5,13 @@
    "metadata": {},
    "source": [
     "# Introduction to DataFrames\n",
-    "**[Bogumił Kamiński](http://bogumilkaminski.pl/about/), May 23, 2018**"
+    "**[Bogumił Kamiński](http://bogumilkaminski.pl/about/), July 25, 2018**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "using DataFrames # load package"
@@ -122,75 +120,28 @@
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "A\n",
-      "Summary Stats:\n",
-      "Mean:           1.500000\n",
-      "Minimum:        1.000000\n",
-      "1st Quartile:   1.250000\n",
-      "Median:         1.500000\n",
-      "3rd Quartile:   1.750000\n",
-      "Maximum:        2.000000\n",
-      "Length:         2\n",
-      "Type:           Int64\n",
-      "\n",
-      "B\n",
-      "Summary Stats:\n",
-      "Mean:           1.000000\n",
-      "Minimum:        1.000000\n",
-      "1st Quartile:   1.000000\n",
-      "Median:         1.000000\n",
-      "3rd Quartile:   1.000000\n",
-      "Maximum:        1.000000\n",
-      "Length:         2\n",
-      "Type:           Union{Float64, Missings.Missing}\n",
-      "Number Missing: 1\n",
-      "% Missing:      50.000000\n",
-      "\n",
-      "C\n",
-      "Summary Stats:\n",
-      "Length:         2\n",
-      "Type:           String\n",
-      "Number Unique:  2\n",
-      "\n"
-     ]
+     "data": {
+      "text/html": [
+       "<table class=\"data-frame\"><thead><tr><th></th><th>variable</th><th>mean</th><th>min</th><th>median</th><th>max</th><th>nunique</th><th>nmissing</th><th>eltype</th></tr></thead><tbody><tr><th>1</th><td>A</td><td>1.5</td><td>1</td><td>1.5</td><td>2</td><td></td><td></td><td>Int64</td></tr><tr><th>2</th><td>B</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td></td><td>1</td><td>Float64</td></tr><tr><th>3</th><td>C</td><td></td><td>a</td><td></td><td>b</td><td>2</td><td></td><td>String</td></tr></tbody></table>"
+      ],
+      "text/plain": [
+       "3×8 DataFrames.DataFrame\n",
+       "│ Row │ variable │ mean │ min │ median │ max │ nunique │ nmissing │ eltype  │\n",
+       "├─────┼──────────┼──────┼─────┼────────┼─────┼─────────┼──────────┼─────────┤\n",
+       "│ 1   │ A        │ 1.5  │ 1   │ 1.5    │ 2   │         │          │ Int64   │\n",
+       "│ 2   │ B        │ 1.0  │ 1.0 │ 1.0    │ 1.0 │         │ 1        │ Float64 │\n",
+       "│ 3   │ C        │      │ a   │        │ b   │ 2       │          │ String  │"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
     "describe(x)"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Use `showcols` to get informaton about columns stored in a DataFrame."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2×3 DataFrames.DataFrame\n",
-      "│ Col # │ Name │ Eltype                           │ Missing │ Values          │\n",
-      "├───────┼──────┼──────────────────────────────────┼─────────┼─────────────────┤\n",
-      "│ 1     │ A    │ Int64                            │ 0       │ 1  …  2         │\n",
-      "│ 2     │ B    │ Union{Float64, Missings.Missing} │ 1       │ 1.0  …  missing │\n",
-      "│ 3     │ C    │ String                           │ 0       │ a  …  b         │"
-     ]
-    }
-   ],
-   "source": [
-    "showcols(x)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -200,7 +151,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -212,7 +163,7 @@
        " :C"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -221,6 +172,13 @@
     "names(x)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Future tip: In Julia 0.7 `propertynames` is also supported."
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -230,7 +188,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -242,7 +200,7 @@
        " String                          "
       ]
      },
-     "execution_count": 8,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -260,10 +218,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 8,
+   "metadata": {},
    "outputs": [],
    "source": [
     "y = DataFrame(rand(1:10, 1000, 10));"
@@ -278,27 +234,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>x1</th><th>x2</th><th>x3</th><th>x4</th><th>x5</th><th>x6</th><th>x7</th><th>x8</th><th>x9</th><th>x10</th></tr></thead><tbody><tr><th>1</th><td>8</td><td>6</td><td>1</td><td>2</td><td>7</td><td>10</td><td>5</td><td>1</td><td>5</td><td>10</td></tr><tr><th>2</th><td>8</td><td>9</td><td>6</td><td>6</td><td>10</td><td>4</td><td>9</td><td>3</td><td>10</td><td>9</td></tr><tr><th>3</th><td>5</td><td>1</td><td>4</td><td>3</td><td>10</td><td>5</td><td>1</td><td>10</td><td>5</td><td>9</td></tr><tr><th>4</th><td>2</td><td>9</td><td>2</td><td>2</td><td>5</td><td>7</td><td>7</td><td>9</td><td>9</td><td>5</td></tr><tr><th>5</th><td>4</td><td>8</td><td>4</td><td>10</td><td>8</td><td>5</td><td>1</td><td>2</td><td>1</td><td>10</td></tr><tr><th>6</th><td>8</td><td>6</td><td>6</td><td>8</td><td>3</td><td>3</td><td>3</td><td>6</td><td>8</td><td>6</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>x1</th><th>x2</th><th>x3</th><th>x4</th><th>x5</th><th>x6</th><th>x7</th><th>x8</th><th>x9</th><th>x10</th></tr></thead><tbody><tr><th>1</th><td>4</td><td>1</td><td>2</td><td>8</td><td>10</td><td>7</td><td>5</td><td>1</td><td>8</td><td>3</td></tr><tr><th>2</th><td>5</td><td>6</td><td>6</td><td>3</td><td>2</td><td>4</td><td>9</td><td>10</td><td>10</td><td>4</td></tr><tr><th>3</th><td>3</td><td>5</td><td>4</td><td>8</td><td>4</td><td>4</td><td>4</td><td>6</td><td>6</td><td>9</td></tr><tr><th>4</th><td>8</td><td>8</td><td>2</td><td>6</td><td>7</td><td>3</td><td>6</td><td>4</td><td>10</td><td>6</td></tr><tr><th>5</th><td>1</td><td>2</td><td>6</td><td>10</td><td>4</td><td>7</td><td>7</td><td>7</td><td>5</td><td>4</td></tr><tr><th>6</th><td>5</td><td>7</td><td>9</td><td>10</td><td>5</td><td>1</td><td>6</td><td>2</td><td>3</td><td>4</td></tr></tbody></table>"
       ],
       "text/plain": [
        "6×10 DataFrames.DataFrame\n",
        "│ Row │ x1 │ x2 │ x3 │ x4 │ x5 │ x6 │ x7 │ x8 │ x9 │ x10 │\n",
        "├─────┼────┼────┼────┼────┼────┼────┼────┼────┼────┼─────┤\n",
-       "│ 1   │ 8  │ 6  │ 1  │ 2  │ 7  │ 10 │ 5  │ 1  │ 5  │ 10  │\n",
-       "│ 2   │ 8  │ 9  │ 6  │ 6  │ 10 │ 4  │ 9  │ 3  │ 10 │ 9   │\n",
-       "│ 3   │ 5  │ 1  │ 4  │ 3  │ 10 │ 5  │ 1  │ 10 │ 5  │ 9   │\n",
-       "│ 4   │ 2  │ 9  │ 2  │ 2  │ 5  │ 7  │ 7  │ 9  │ 9  │ 5   │\n",
-       "│ 5   │ 4  │ 8  │ 4  │ 10 │ 8  │ 5  │ 1  │ 2  │ 1  │ 10  │\n",
-       "│ 6   │ 8  │ 6  │ 6  │ 8  │ 3  │ 3  │ 3  │ 6  │ 8  │ 6   │"
+       "│ 1   │ 4  │ 1  │ 2  │ 8  │ 10 │ 7  │ 5  │ 1  │ 8  │ 3   │\n",
+       "│ 2   │ 5  │ 6  │ 6  │ 3  │ 2  │ 4  │ 9  │ 10 │ 10 │ 4   │\n",
+       "│ 3   │ 3  │ 5  │ 4  │ 8  │ 4  │ 4  │ 4  │ 6  │ 6  │ 9   │\n",
+       "│ 4   │ 8  │ 8  │ 2  │ 6  │ 7  │ 3  │ 6  │ 4  │ 10 │ 6   │\n",
+       "│ 5   │ 1  │ 2  │ 6  │ 10 │ 4  │ 7  │ 7  │ 7  │ 5  │ 4   │\n",
+       "│ 6   │ 5  │ 7  │ 9  │ 10 │ 5  │ 1  │ 6  │ 2  │ 3  │ 4   │"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -316,24 +272,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>x1</th><th>x2</th><th>x3</th><th>x4</th><th>x5</th><th>x6</th><th>x7</th><th>x8</th><th>x9</th><th>x10</th></tr></thead><tbody><tr><th>1</th><td>1</td><td>10</td><td>5</td><td>7</td><td>8</td><td>6</td><td>1</td><td>2</td><td>3</td><td>6</td></tr><tr><th>2</th><td>1</td><td>1</td><td>2</td><td>7</td><td>9</td><td>7</td><td>3</td><td>3</td><td>3</td><td>3</td></tr><tr><th>3</th><td>4</td><td>6</td><td>1</td><td>2</td><td>1</td><td>1</td><td>4</td><td>7</td><td>9</td><td>4</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>x1</th><th>x2</th><th>x3</th><th>x4</th><th>x5</th><th>x6</th><th>x7</th><th>x8</th><th>x9</th><th>x10</th></tr></thead><tbody><tr><th>1</th><td>2</td><td>8</td><td>3</td><td>7</td><td>6</td><td>4</td><td>3</td><td>8</td><td>5</td><td>4</td></tr><tr><th>2</th><td>7</td><td>1</td><td>5</td><td>5</td><td>3</td><td>6</td><td>1</td><td>8</td><td>5</td><td>1</td></tr><tr><th>3</th><td>8</td><td>1</td><td>10</td><td>9</td><td>4</td><td>2</td><td>10</td><td>2</td><td>6</td><td>6</td></tr></tbody></table>"
       ],
       "text/plain": [
        "3×10 DataFrames.DataFrame\n",
        "│ Row │ x1 │ x2 │ x3 │ x4 │ x5 │ x6 │ x7 │ x8 │ x9 │ x10 │\n",
        "├─────┼────┼────┼────┼────┼────┼────┼────┼────┼────┼─────┤\n",
-       "│ 1   │ 1  │ 10 │ 5  │ 7  │ 8  │ 6  │ 1  │ 2  │ 3  │ 6   │\n",
-       "│ 2   │ 1  │ 1  │ 2  │ 7  │ 9  │ 7  │ 3  │ 3  │ 3  │ 3   │\n",
-       "│ 3   │ 4  │ 6  │ 1  │ 2  │ 1  │ 1  │ 4  │ 7  │ 9  │ 4   │"
+       "│ 1   │ 2  │ 8  │ 3  │ 7  │ 6  │ 4  │ 3  │ 8  │ 5  │ 4   │\n",
+       "│ 2   │ 7  │ 1  │ 5  │ 5  │ 3  │ 6  │ 1  │ 8  │ 5  │ 1   │\n",
+       "│ 3   │ 8  │ 1  │ 10 │ 9  │ 4  │ 2  │ 10 │ 2  │ 6  │ 6   │"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -353,7 +309,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -362,7 +318,7 @@
        "([1, 2], [1, 2], [1, 2])"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -371,6 +327,13 @@
     "x[1], x[:A], x[:, 1]"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Future tip: In Julia 0.7 also accessing column using `x.A` syntax (`getproperty`/`setproperty!`) is supported."
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -380,7 +343,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -395,7 +358,7 @@
        "│ 1   │ 1 │ 1.0 │ a │"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -413,7 +376,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -422,7 +385,7 @@
        "1"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -440,7 +403,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -456,7 +419,7 @@
        "│ 2   │ 1 │ 1.0 │ b │"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -475,7 +438,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -491,7 +454,7 @@
        "│ 2   │ 2 │ 2.0 │ b │"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -510,7 +473,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -526,7 +489,7 @@
        "│ 2   │ 7 │ 8.0 │ b │"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -539,7 +502,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Julia 0.6.0",
+   "display_name": "Julia 0.6.2",
    "language": "julia",
    "name": "julia-0.6"
   },
@@ -547,7 +510,7 @@
    "file_extension": ".jl",
    "mimetype": "application/julia",
    "name": "julia",
-   "version": "0.6.0"
+   "version": "0.6.3"
   }
  },
  "nbformat": 4,
diff --git a/03_missingvalues.ipynb b/03_missingvalues.ipynb
index 44abc5b..c580a08 100644
--- a/03_missingvalues.ipynb
+++ b/03_missingvalues.ipynb
@@ -5,7 +5,7 @@
    "metadata": {},
    "source": [
     "# Introduction to DataFrames\n",
-    "**[Bogumił Kamiński](http://bogumilkaminski.pl/about/), May 23, 2018**"
+    "**[Bogumił Kamiński](http://bogumilkaminski.pl/about/), July 25, 2018**"
    ]
   },
   {
@@ -391,7 +391,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Caution: `nothing` would also be replaced here (for Julia 0.7 a more sophisticated behavior of `coalesce` that allows to avoid this problem is planned)."
+    "Future tip:: `nothing` would also be replaced here (for Julia 0.7 `coalesce` will only handle `missing`)."
    ]
   },
   {
@@ -641,7 +641,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "When we call `showcols` on a `DataFrame` with dropped missing values, the columns still allow missing values."
+    "When we call `describe` on a `DataFrame` with dropped missing values, the columns still allow missing values."
    ]
   },
   {
@@ -650,48 +650,60 @@
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2×2 DataFrames.DataFrame\n",
-      "│ Col # │ Name │ Eltype                          │ Missing │ Values  │\n",
-      "├───────┼──────┼─────────────────────────────────┼─────────┼─────────┤\n",
-      "│ 1     │ A    │ Union{Int64, Missings.Missing}  │ 0       │ 1  …  4 │\n",
-      "│ 2     │ B    │ Union{Missings.Missing, String} │ 0       │ A  …  C │"
-     ]
+     "data": {
+      "text/html": [
+       "<table class=\"data-frame\"><thead><tr><th></th><th>variable</th><th>mean</th><th>min</th><th>median</th><th>max</th><th>nunique</th><th>nmissing</th><th>eltype</th></tr></thead><tbody><tr><th>1</th><td>A</td><td>2.5</td><td>1</td><td>2.5</td><td>4</td><td></td><td>0</td><td>Int64</td></tr><tr><th>2</th><td>B</td><td></td><td>A</td><td></td><td>C</td><td>2</td><td>0</td><td>String</td></tr></tbody></table>"
+      ],
+      "text/plain": [
+       "2×8 DataFrames.DataFrame\n",
+       "│ Row │ variable │ mean │ min │ median │ max │ nunique │ nmissing │ eltype │\n",
+       "├─────┼──────────┼──────┼─────┼────────┼─────┼─────────┼──────────┼────────┤\n",
+       "│ 1   │ A        │ 2.5  │ 1   │ 2.5    │ 4   │         │ 0        │ Int64  │\n",
+       "│ 2   │ B        │      │ A   │        │ C   │ 2       │ 0        │ String │"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
-    "showcols(x)"
+    "describe(x)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Since we've excluded missing values, we can safely use `disallowmissing!` so that the columns will no longer accept missing values."
+    "Since we've excluded missing values, we can safely use `disallowmissing!` so that the columns will no longer accept missing values (we can see this as `nmissing` column is empty)."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2×2 DataFrames.DataFrame\n",
-      "│ Col # │ Name │ Eltype │ Missing │ Values  │\n",
-      "├───────┼──────┼────────┼─────────┼─────────┤\n",
-      "│ 1     │ A    │ Int64  │ 0       │ 1  …  4 │\n",
-      "│ 2     │ B    │ String │ 0       │ A  …  C │"
-     ]
+     "data": {
+      "text/html": [
+       "<table class=\"data-frame\"><thead><tr><th></th><th>variable</th><th>mean</th><th>min</th><th>median</th><th>max</th><th>nunique</th><th>nmissing</th><th>eltype</th></tr></thead><tbody><tr><th>1</th><td>A</td><td>2.5</td><td>1</td><td>2.5</td><td>4</td><td></td><td></td><td>Int64</td></tr><tr><th>2</th><td>B</td><td></td><td>A</td><td></td><td>C</td><td>2</td><td></td><td>String</td></tr></tbody></table>"
+      ],
+      "text/plain": [
+       "2×8 DataFrames.DataFrame\n",
+       "│ Row │ variable │ mean │ min │ median │ max │ nunique │ nmissing │ eltype │\n",
+       "├─────┼──────────┼──────┼─────┼────────┼─────┼─────────┼──────────┼────────┤\n",
+       "│ 1   │ A        │ 2.5  │ 1   │ 2.5    │ 4   │         │          │ Int64  │\n",
+       "│ 2   │ B        │      │ A   │        │ C   │ 2       │          │ String │"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
     "disallowmissing!(x)\n",
-    "showcols(x)"
+    "describe(x)"
    ]
   }
  ],
@@ -705,7 +717,7 @@
    "file_extension": ".jl",
    "mimetype": "application/julia",
    "name": "julia",
-   "version": "0.6.2"
+   "version": "0.6.3"
   }
  },
  "nbformat": 4,
diff --git a/04_loadsave.ipynb b/04_loadsave.ipynb
index b6b1a1e..8ca3145 100644
--- a/04_loadsave.ipynb
+++ b/04_loadsave.ipynb
@@ -5,15 +5,13 @@
    "metadata": {},
    "source": [
     "# Introduction to DataFrames\n",
-    "**[Bogumił Kamiński](http://bogumilkaminski.pl/about/), May 23, 2018**"
+    "**[Bogumił Kamiński](http://bogumilkaminski.pl/about/), July 25, 2018**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "using DataFrames # load package"
@@ -32,9 +30,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "using CSV\n",
@@ -131,7 +127,8 @@
        "        dateformat: nothing\n",
        "        decimal: '.'\n",
        "        truestring: 'true'\n",
-       "        falsestring: 'false', IOBuffer(data=UInt8[...], readable=true, writable=true, seekable=true, append=false, size=0, maxsize=Inf, ptr=1, mark=-1), \"x.csv\", 8, true, String[\"A\", \"B\", \"C\", \"D\"], 4, false, Val{false})"
+       "        falsestring: 'false'\n",
+       "        internstrings: true, IOBuffer(data=UInt8[...], readable=true, writable=true, seekable=true, append=false, size=0, maxsize=Inf, ptr=1, mark=-1), \"x.csv\", 8, true, String[\"A\", \"B\", \"C\", \"D\"], 4, false, Val{false})"
       ]
      },
      "execution_count": 5,
@@ -246,9 +243,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "save(\"x.jld\", \"x\", x)"
@@ -338,15 +333,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "  0.782157 seconds (688.90 k allocations: 30.828 MiB, 1.08% gc time)\n",
-      "  0.018250 seconds (203.61 k allocations: 3.339 MiB)\n"
+      "  2.529390 seconds (936.79 k allocations: 44.927 MiB, 0.83% gc time)\n",
+      "  0.018948 seconds (203.62 k allocations: 3.339 MiB)\n"
      ]
     },
     {
      "data": {
       "text/plain": [
        "2-element Array{Int64,1}:\n",
-       " 595307\n",
+       " 595456\n",
        " 154487"
       ]
      },
@@ -372,9 +367,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "foreach(rm, [\"x.csv\", \"x.jld\", \"bigdf.csv\", \"bigdf.jld\"])"
@@ -383,7 +376,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Julia 0.6.0",
+   "display_name": "Julia 0.6.2",
    "language": "julia",
    "name": "julia-0.6"
   },
@@ -391,7 +384,7 @@
    "file_extension": ".jl",
    "mimetype": "application/julia",
    "name": "julia",
-   "version": "0.6.0"
+   "version": "0.6.3"
   }
  },
  "nbformat": 4,
diff --git a/05_columns.ipynb b/05_columns.ipynb
index e9c4ab6..2790a92 100644
--- a/05_columns.ipynb
+++ b/05_columns.ipynb
@@ -5,15 +5,13 @@
    "metadata": {},
    "source": [
     "# Introduction to DataFrames\n",
-    "**[Bogumił Kamiński](http://bogumilkaminski.pl/about/), May 23, 2018**"
+    "**[Bogumił Kamiński](http://bogumilkaminski.pl/about/), July 25, 2018**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "using DataFrames # load package"
@@ -43,7 +41,7 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>x1</th><th>x2</th><th>x3</th><th>x4</th></tr></thead><tbody><tr><th>1</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>2</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>3</th><td>false</td><td>false</td><td>false</td><td>false</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>x1</th><th>x2</th><th>x3</th><th>x4</th></tr></thead><tbody><tr><th>1</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>2</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>3</th><td>true</td><td>true</td><td>true</td><td>false</td></tr></tbody></table>"
       ],
       "text/plain": [
        "3×4 DataFrames.DataFrame\n",
@@ -51,7 +49,7 @@
        "├─────┼───────┼───────┼───────┼───────┤\n",
        "│ 1   │ false │ false │ false │ false │\n",
        "│ 2   │ false │ false │ false │ false │\n",
-       "│ 3   │ false │ false │ false │ false │"
+       "│ 3   │ true  │ true  │ true  │ false │"
       ]
      },
      "execution_count": 2,
@@ -78,7 +76,7 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>A</th><th>x2</th><th>x3</th><th>x4</th></tr></thead><tbody><tr><th>1</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>2</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>3</th><td>false</td><td>false</td><td>false</td><td>false</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>A</th><th>x2</th><th>x3</th><th>x4</th></tr></thead><tbody><tr><th>1</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>2</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>3</th><td>true</td><td>true</td><td>true</td><td>false</td></tr></tbody></table>"
       ],
       "text/plain": [
        "3×4 DataFrames.DataFrame\n",
@@ -86,7 +84,7 @@
        "├─────┼───────┼───────┼───────┼───────┤\n",
        "│ 1   │ false │ false │ false │ false │\n",
        "│ 2   │ false │ false │ false │ false │\n",
-       "│ 3   │ false │ false │ false │ false │"
+       "│ 3   │ true  │ true  │ true  │ false │"
       ]
      },
      "execution_count": 3,
@@ -115,7 +113,7 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>x1x1</th><th>x2x2</th><th>x3x3</th><th>x4x4</th></tr></thead><tbody><tr><th>1</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>2</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>3</th><td>false</td><td>false</td><td>false</td><td>false</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>x1x1</th><th>x2x2</th><th>x3x3</th><th>x4x4</th></tr></thead><tbody><tr><th>1</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>2</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>3</th><td>true</td><td>true</td><td>true</td><td>false</td></tr></tbody></table>"
       ],
       "text/plain": [
        "3×4 DataFrames.DataFrame\n",
@@ -123,7 +121,7 @@
        "├─────┼───────┼───────┼───────┼───────┤\n",
        "│ 1   │ false │ false │ false │ false │\n",
        "│ 2   │ false │ false │ false │ false │\n",
-       "│ 3   │ false │ false │ false │ false │"
+       "│ 3   │ true  │ true  │ true  │ false │"
       ]
      },
      "execution_count": 4,
@@ -152,7 +150,7 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>x1x1</th><th>x2x2</th><th>third</th><th>x4x4</th></tr></thead><tbody><tr><th>1</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>2</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>3</th><td>false</td><td>false</td><td>false</td><td>false</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>x1x1</th><th>x2x2</th><th>third</th><th>x4x4</th></tr></thead><tbody><tr><th>1</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>2</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>3</th><td>true</td><td>true</td><td>true</td><td>false</td></tr></tbody></table>"
       ],
       "text/plain": [
        "3×4 DataFrames.DataFrame\n",
@@ -160,7 +158,7 @@
        "├─────┼───────┼───────┼───────┼───────┤\n",
        "│ 1   │ false │ false │ false │ false │\n",
        "│ 2   │ false │ false │ false │ false │\n",
-       "│ 3   │ false │ false │ false │ false │"
+       "│ 3   │ true  │ true  │ true  │ false │"
       ]
      },
      "execution_count": 5,
@@ -187,7 +185,7 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>a</th><th>b</th><th>c</th><th>d</th></tr></thead><tbody><tr><th>1</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>2</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>3</th><td>false</td><td>false</td><td>false</td><td>false</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>a</th><th>b</th><th>c</th><th>d</th></tr></thead><tbody><tr><th>1</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>2</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>3</th><td>true</td><td>true</td><td>true</td><td>false</td></tr></tbody></table>"
       ],
       "text/plain": [
        "3×4 DataFrames.DataFrame\n",
@@ -195,7 +193,7 @@
        "├─────┼───────┼───────┼───────┼───────┤\n",
        "│ 1   │ false │ false │ false │ false │\n",
        "│ 2   │ false │ false │ false │ false │\n",
-       "│ 3   │ false │ false │ false │ false │"
+       "│ 3   │ true  │ true  │ true  │ false │"
       ]
      },
      "execution_count": 6,
@@ -253,7 +251,7 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>a</th><th>a_1</th><th>a_2</th><th>a_3</th></tr></thead><tbody><tr><th>1</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>2</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>3</th><td>false</td><td>false</td><td>false</td><td>false</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>a</th><th>a_1</th><th>a_2</th><th>a_3</th></tr></thead><tbody><tr><th>1</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>2</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>3</th><td>true</td><td>true</td><td>true</td><td>false</td></tr></tbody></table>"
       ],
       "text/plain": [
        "3×4 DataFrames.DataFrame\n",
@@ -261,7 +259,7 @@
        "├─────┼───────┼───────┼───────┼───────┤\n",
        "│ 1   │ false │ false │ false │ false │\n",
        "│ 2   │ false │ false │ false │ false │\n",
-       "│ 3   │ false │ false │ false │ false │"
+       "│ 3   │ true  │ true  │ true  │ false │"
       ]
      },
      "execution_count": 8,
@@ -297,7 +295,7 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>a_1</th><th>a_3</th><th>a_2</th><th>a</th></tr></thead><tbody><tr><th>1</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>2</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>3</th><td>false</td><td>false</td><td>false</td><td>false</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>a_1</th><th>a_3</th><th>a_2</th><th>a</th></tr></thead><tbody><tr><th>1</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>2</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>3</th><td>true</td><td>false</td><td>true</td><td>true</td></tr></tbody></table>"
       ],
       "text/plain": [
        "3×4 DataFrames.DataFrame\n",
@@ -305,7 +303,7 @@
        "├─────┼───────┼───────┼───────┼───────┤\n",
        "│ 1   │ false │ false │ false │ false │\n",
        "│ 2   │ false │ false │ false │ false │\n",
-       "│ 3   │ false │ false │ false │ false │"
+       "│ 3   │ true  │ false │ true  │ true  │"
       ]
      },
      "execution_count": 9,
@@ -322,7 +320,35 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "also `permutecols!` will be introduced in next release of DataFrames"
+    "Also `permutecols!` can be used to achieve this in place:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<table class=\"data-frame\"><thead><tr><th></th><th>a_3</th><th>a_2</th><th>a_1</th><th>a</th></tr></thead><tbody><tr><th>1</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>2</th><td>false</td><td>false</td><td>false</td><td>false</td></tr><tr><th>3</th><td>false</td><td>true</td><td>true</td><td>true</td></tr></tbody></table>"
+      ],
+      "text/plain": [
+       "3×4 DataFrames.DataFrame\n",
+       "│ Row │ a_3   │ a_2   │ a_1   │ a     │\n",
+       "├─────┼───────┼───────┼───────┼───────┤\n",
+       "│ 1   │ false │ false │ false │ false │\n",
+       "│ 2   │ false │ false │ false │ false │\n",
+       "│ 3   │ false │ true  │ true  │ true  │"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "permutecols!(x, 4:-1:1); x"
    ]
   },
   {
@@ -334,7 +360,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -351,7 +377,7 @@
        "│ 3   │ (3, 1) │ (3, 2) │ (3, 3) │ (3, 4) │"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -369,7 +395,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -386,7 +412,7 @@
        "│ 3   │ (3, 1) │ (3, 2) │ (3, 3) │ (3, 4) │ (3, 1) │ (3, 2) │ (3, 3) │ (3, 4) │"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -404,7 +430,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -421,7 +447,7 @@
        "│ 3   │ (3, 1) │ (3, 2) │ (3, 3) │ (3, 4) │ 3    │"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -439,7 +465,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -456,7 +482,7 @@
        "│ 3   │ 3  │ (3, 1) │ (3, 2) │ (3, 3) │ (3, 4) │"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -474,7 +500,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -491,7 +517,7 @@
        "│ 3   │ (3, 1) │ (3, 2) │ (3, 3) │ (3, 4) │ 3 │"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -509,7 +535,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -526,7 +552,7 @@
        "│ 3   │ 3 │ (3, 1) │ (3, 2) │ (3, 3) │ (3, 4) │"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -544,14 +570,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "  20.993 μs (133 allocations: 10.20 KiB)\n"
+      "  21.460 μs (133 allocations: 10.20 KiB)\n"
      ]
     },
     {
@@ -568,7 +594,7 @@
        "│ 3   │ (3, 1) │ (3, 2) │ 3 │ (3, 3) │ (3, 4) │"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -587,7 +613,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -604,7 +630,7 @@
        "│ 3   │ 3 │ 3      │ (3, 1) │ (3, 2) │ (3, 3) │ (3, 4) │"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -622,7 +648,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -639,7 +665,7 @@
        "│ 3   │ 3 │ 3        │ 3      │ (3, 1) │ (3, 2) │ (3, 3) │ (3, 4) │"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -657,7 +683,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -681,7 +707,7 @@
        "│ 3   │ (3, 1) │ (3, 2) │ 3 │ (3, 3) │ (3, 4) │"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -699,7 +725,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -716,7 +742,7 @@
        "│ 3   │ (3, 1) │ (3, 2) │ (3, 3) │ (3, 4) │ 3 │"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -734,7 +760,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -751,7 +777,7 @@
        "│ 3   │ 3 │ (3, 1) │ (3, 2) │ (3, 3) │ (3, 4) │ 3 │"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -769,7 +795,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -793,7 +819,7 @@
        "│ 3   │ 'c' │ 6 │ 'f' │ 13  │)"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -813,7 +839,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -830,7 +856,7 @@
        "│ 3   │ 3 │ 6 │ 'c' │ 'f' │ 13  │"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -852,7 +878,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
@@ -869,7 +895,7 @@
        "│ 3   │ (3, 1) │ (3, 2) │ (3, 3) │ (3, 4) │ (3, 5) │"
       ]
      },
-     "execution_count": 24,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -887,7 +913,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
@@ -904,7 +930,7 @@
        "│ 3   │ (3, 1) │ (3, 2) │ (3, 4) │ (3, 5) │"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -922,7 +948,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -939,7 +965,7 @@
        "│ 3   │ (3, 1) │ (3, 4) │"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -957,7 +983,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
@@ -974,7 +1000,7 @@
        "│ 3   │ (3, 1) │ (3, 3) │ (3, 5) │"
       ]
      },
-     "execution_count": 27,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -992,7 +1018,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [
     {
@@ -1009,7 +1035,7 @@
        "│ 3   │ (3, 1) │"
       ]
      },
-     "execution_count": 28,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1027,7 +1053,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
@@ -1039,7 +1065,7 @@
        " (3, 1)"
       ]
      },
-     "execution_count": 29,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1057,7 +1083,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
@@ -1069,7 +1095,7 @@
        " (3, 1)"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1087,7 +1113,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
@@ -1099,7 +1125,7 @@
        "0×0 DataFrames.DataFrame\n"
       ]
      },
-     "execution_count": 31,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1117,7 +1143,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
@@ -1136,7 +1162,7 @@
        "│ 3   │ (3, 1) │ (3, 2) │ (3, 4) │ (3, 5) │)"
       ]
      },
-     "execution_count": 32,
+     "execution_count": 33,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1155,7 +1181,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [
     {
@@ -1172,7 +1198,7 @@
        "│ 3   │ (3, 1) │ (3, 2) │ (3, 3) │ (3, 4) │ (3, 5) │"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 34,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1190,7 +1216,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
@@ -1207,7 +1233,7 @@
        "│ 3   │ (3, 2) │ (3, 2) │ (3, 3) │ (3, 4) │ (3, 5) │"
       ]
      },
-     "execution_count": 34,
+     "execution_count": 35,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1226,7 +1252,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
@@ -1243,7 +1269,7 @@
        "│ 3   │ (3, 2) │ (3, 2) │ (3, 3) │ (3, 4) │ (3, 5) │ 3 │"
       ]
      },
-     "execution_count": 35,
+     "execution_count": 36,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1262,7 +1288,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
@@ -1279,7 +1305,7 @@
        "│ 3   │ (3, 2) │ (3, 2) │ (3, 3) │ (3, 4) │ (3, 5) │ 3 │ 13 │"
       ]
      },
-     "execution_count": 36,
+     "execution_count": 37,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1298,7 +1324,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [
     {
@@ -1315,7 +1341,7 @@
        "│ 3   │ (3, 1) │ (3, 2) │ (3, 3) │ (3, 4) │ (3, 5) │"
       ]
      },
-     "execution_count": 37,
+     "execution_count": 38,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1333,7 +1359,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [
     {
@@ -1342,7 +1368,7 @@
        "true"
       ]
      },
-     "execution_count": 38,
+     "execution_count": 39,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1360,7 +1386,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {
@@ -1369,7 +1395,7 @@
        "2"
       ]
      },
-     "execution_count": 39,
+     "execution_count": 40,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1381,7 +1407,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Julia 0.6.0",
+   "display_name": "Julia 0.6.2",
    "language": "julia",
    "name": "julia-0.6"
   },
@@ -1389,7 +1415,7 @@
    "file_extension": ".jl",
    "mimetype": "application/julia",
    "name": "julia",
-   "version": "0.6.0"
+   "version": "0.6.3"
   }
  },
  "nbformat": 4,
diff --git a/08_joins.ipynb b/08_joins.ipynb
index 2d273be..60b83f1 100644
--- a/08_joins.ipynb
+++ b/08_joins.ipynb
@@ -5,7 +5,7 @@
    "metadata": {},
    "source": [
     "# Introduction to DataFrames\n",
-    "**[Bogumił Kamiński](http://bogumilkaminski.pl/about/), Apr 21, 2017**"
+    "**[Bogumił Kamiński](http://bogumilkaminski.pl/about/), July 25, 2017**"
    ]
   },
   {
@@ -417,20 +417,24 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"data-frame\"><thead><tr><th></th><th>id1</th><th>id2</th><th>name</th><th>id2_1</th><th>age</th></tr></thead><tbody><tr><th>1</th><td>1</td><td>1</td><td>Alice</td><td>11</td><td>21</td></tr><tr><th>2</th><td>1</td><td>1</td><td>Alice</td><td>1</td><td>22</td></tr><tr><th>3</th><td>1</td><td>11</td><td>Bob</td><td>11</td><td>21</td></tr><tr><th>4</th><td>1</td><td>11</td><td>Bob</td><td>1</td><td>22</td></tr><tr><th>5</th><td>missing</td><td>missing</td><td>Zed</td><td>missing</td><td>99</td></tr><tr><th>6</th><td>missing</td><td>missing</td><td>Zed</td><td>999</td><td>100</td></tr><tr><th>7</th><td>missing</td><td>99</td><td>Zoe</td><td>missing</td><td>99</td></tr><tr><th>8</th><td>missing</td><td>99</td><td>Zoe</td><td>999</td><td>100</td></tr></tbody></table>"
+       "<table class=\"data-frame\"><thead><tr><th></th><th>id1</th><th>id2</th><th>name</th><th>id2_1</th><th>age</th><th>source</th></tr></thead><tbody><tr><th>1</th><td>1</td><td>1</td><td>Alice</td><td>11</td><td>21</td><td>both</td></tr><tr><th>2</th><td>1</td><td>1</td><td>Alice</td><td>1</td><td>22</td><td>both</td></tr><tr><th>3</th><td>1</td><td>11</td><td>Bob</td><td>11</td><td>21</td><td>both</td></tr><tr><th>4</th><td>1</td><td>11</td><td>Bob</td><td>1</td><td>22</td><td>both</td></tr><tr><th>5</th><td>2</td><td>2</td><td>Conor</td><td>missing</td><td>missing</td><td>left_only</td></tr><tr><th>6</th><td>2</td><td>21</td><td>Dave</td><td>missing</td><td>missing</td><td>left_only</td></tr><tr><th>7</th><td>missing</td><td>missing</td><td>Zed</td><td>missing</td><td>99</td><td>both</td></tr><tr><th>8</th><td>missing</td><td>missing</td><td>Zed</td><td>999</td><td>100</td><td>both</td></tr><tr><th>9</th><td>missing</td><td>99</td><td>Zoe</td><td>missing</td><td>99</td><td>both</td></tr><tr><th>10</th><td>missing</td><td>99</td><td>Zoe</td><td>999</td><td>100</td><td>both</td></tr><tr><th>11</th><td>3</td><td>missing</td><td>missing</td><td>31</td><td>23</td><td>right_only</td></tr><tr><th>12</th><td>3</td><td>missing</td><td>missing</td><td>3</td><td>24</td><td>right_only</td></tr></tbody></table>"
       ],
       "text/plain": [
-       "8×5 DataFrames.DataFrame\n",
-       "│ Row │ id1     │ id2     │ name  │ id2_1   │ age │\n",
-       "├─────┼─────────┼─────────┼───────┼─────────┼─────┤\n",
-       "│ 1   │ 1       │ 1       │ Alice │ 11      │ 21  │\n",
-       "│ 2   │ 1       │ 1       │ Alice │ 1       │ 22  │\n",
-       "│ 3   │ 1       │ 11      │ Bob   │ 11      │ 21  │\n",
-       "│ 4   │ 1       │ 11      │ Bob   │ 1       │ 22  │\n",
-       "│ 5   │ \u001b[90mmissing\u001b[39m │ \u001b[90mmissing\u001b[39m │ Zed   │ \u001b[90mmissing\u001b[39m │ 99  │\n",
-       "│ 6   │ \u001b[90mmissing\u001b[39m │ \u001b[90mmissing\u001b[39m │ Zed   │ 999     │ 100 │\n",
-       "│ 7   │ \u001b[90mmissing\u001b[39m │ 99      │ Zoe   │ \u001b[90mmissing\u001b[39m │ 99  │\n",
-       "│ 8   │ \u001b[90mmissing\u001b[39m │ 99      │ Zoe   │ 999     │ 100 │"
+       "12×6 DataFrames.DataFrame\n",
+       "│ Row │ id1     │ id2     │ name    │ id2_1   │ age     │ source     │\n",
+       "├─────┼─────────┼─────────┼─────────┼─────────┼─────────┼────────────┤\n",
+       "│ 1   │ 1       │ 1       │ Alice   │ 11      │ 21      │ both       │\n",
+       "│ 2   │ 1       │ 1       │ Alice   │ 1       │ 22      │ both       │\n",
+       "│ 3   │ 1       │ 11      │ Bob     │ 11      │ 21      │ both       │\n",
+       "│ 4   │ 1       │ 11      │ Bob     │ 1       │ 22      │ both       │\n",
+       "│ 5   │ 2       │ 2       │ Conor   │ \u001b[90mmissing\u001b[39m │ \u001b[90mmissing\u001b[39m │ left_only  │\n",
+       "│ 6   │ 2       │ 21      │ Dave    │ \u001b[90mmissing\u001b[39m │ \u001b[90mmissing\u001b[39m │ left_only  │\n",
+       "│ 7   │ \u001b[90mmissing\u001b[39m │ \u001b[90mmissing\u001b[39m │ Zed     │ \u001b[90mmissing\u001b[39m │ 99      │ both       │\n",
+       "│ 8   │ \u001b[90mmissing\u001b[39m │ \u001b[90mmissing\u001b[39m │ Zed     │ 999     │ 100     │ both       │\n",
+       "│ 9   │ \u001b[90mmissing\u001b[39m │ 99      │ Zoe     │ \u001b[90mmissing\u001b[39m │ 99      │ both       │\n",
+       "│ 10  │ \u001b[90mmissing\u001b[39m │ 99      │ Zoe     │ 999     │ 100     │ both       │\n",
+       "│ 11  │ 3       │ \u001b[90mmissing\u001b[39m │ \u001b[90mmissing\u001b[39m │ 31      │ 23      │ right_only │\n",
+       "│ 12  │ 3       │ \u001b[90mmissing\u001b[39m │ \u001b[90mmissing\u001b[39m │ 3       │ 24      │ right_only │"
       ]
      },
      "execution_count": 13,
@@ -439,13 +443,35 @@
     }
    ],
    "source": [
-    "join(x, y, on=[:id1], makeunique=true) # with duplicates all combinations are produced (here :inner join)"
+    "join(x, y, on=[:id1], makeunique=true, kind=:outer, indicator=:source) # with duplicates all combinations are produced"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 14,
    "metadata": {},
+   "outputs": [
+    {
+     "ename": "LoadError",
+     "evalue": "\u001b[91mArgumentError: Merge key(s) are not unique in both df1 and df2. First duplicate in df1 at 2. First duplicate in df2 at 2\u001b[39m",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[91mArgumentError: Merge key(s) are not unique in both df1 and df2. First duplicate in df1 at 2. First duplicate in df2 at 2\u001b[39m",
+      "",
+      "Stacktrace:",
+      " [1] \u001b[1m#join#138\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Array{Symbol,1}, ::Symbol, ::Bool, ::Void, ::Tuple{Bool,Bool}, ::Function, ::DataFrames.DataFrame, ::DataFrames.DataFrame\u001b[1m)\u001b[22m\u001b[22m at \u001b[1mD:\\Software\\JULIA_PKG\\v0.6\\DataFrames\\src\\abstractdataframe\\join.jl:327\u001b[22m\u001b[22m",
+      " [2] \u001b[1m(::Base.#kw##join)\u001b[22m\u001b[22m\u001b[1m(\u001b[22m\u001b[22m::Array{Any,1}, ::Base.#join, ::DataFrames.DataFrame, ::DataFrames.DataFrame\u001b[1m)\u001b[22m\u001b[22m at \u001b[1m.\\<missing>:0\u001b[22m\u001b[22m"
+     ]
+    }
+   ],
+   "source": [
+    "join(x, y, on=[:id1], makeunique=true, validate=(true,true)) # you can force validation of uniqueness of key on which you join"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -462,7 +488,7 @@
        "│ 4   │ \u001b[90mmissing\u001b[39m │ 99      │ Zoe   │"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -482,7 +508,7 @@
    "file_extension": ".jl",
    "mimetype": "application/julia",
    "name": "julia",
-   "version": "0.6.2"
+   "version": "0.6.3"
   }
  },
  "nbformat": 4,
diff --git a/10_transforms.ipynb b/10_transforms.ipynb
index 6bfeb84..8281c3e 100644
--- a/10_transforms.ipynb
+++ b/10_transforms.ipynb
@@ -562,7 +562,7 @@
    "file_extension": ".jl",
    "mimetype": "application/julia",
    "name": "julia",
-   "version": "0.6.2"
+   "version": "0.6.3"
   }
  },
  "nbformat": 4,
diff --git a/README.md b/README.md
index 71e7a3d..9865043 100644
--- a/README.md
+++ b/README.md
@@ -1,9 +1,9 @@
 # An Introduction to DataFrames
 
-[Bogumił Kamiński](http://bogumilkaminski.pl/about/), May 23, 2018
+[Bogumił Kamiński](http://bogumilkaminski.pl/about/), July 25, 2018
 
 A brief introduction to basic usage of [DataFrames](https://github.com/JuliaData/DataFrames.jl).
-Tested under Julia 0.6.2, DataFrames 0.11.6, CSV 0.2.4, JLD 0.8.3, Missings 0.2.9, CategoricalArrays 0.3.9, FreqTables 0.2.2, DataFramesMeta 0.3.0, StatPlots 0.7.2.
+Tested under Julia 0.6.3, DataFrames 0.11.7, CSV 0.2.5, JLD 0.8.3, Missings 0.2.10, CategoricalArrays 0.3.11, FreqTables 0.2.2, DataFramesMeta 0.3.0, StatPlots 0.7.2.
 
 I will try to keep it up to date as the package evolves.
 This tutorial covers
@@ -54,14 +54,15 @@ Changelog:
 | 2018-05-01 | Added `byrow!` example                                                                            |
 | 2018-05-13 | Added `StatPlots` package to extras                                                               |
 | 2018-05-23 | Improved comments in sections 1 do 5 by [Jane Herriman](https://github.com/xorJane)               |
+| 2018-07-25 | Update to 0.11.7 release                                                                          |
 
 # Core functions summary
 
 1. Constructors: `DataFrame`
-2. Getting summary: `size`, `nrow`, `ncol`, `length`, `describe`, `showcols`, `names`, `eltypes`, `head`, `tail`
+2. Getting summary: `size`, `nrow`, `ncol`, `length`, `describe`, `names`, `eltypes`, `head`, `tail`
 3. Handling missing: `missing` (singleton instance of `Missing`), `ismissing`, `Missings.T`, `skipmissing`, `coalesce`, `allowmissing`, `disallowmissing`, `allowmissing!`, `completecases`, `dropmissing`, `dropmissing!`, disallowmissing, disallowmissing!
 4. Loading and saving: `CSV` (package), `JLD` (package), `CSV.read`, `CSV.write`, `save` (from `JLD`), `load` (from `JLD`)
-5. Working with columns: `rename`, `rename!`, `names!`, `hcat`, `insert!`, `DataFrames.hcat!`, `merge!`, `delete!`, `empty!`, `categorical!`, `DataFrames.index`
+5. Working with columns: `rename`, `rename!`, `names!`, `hcat`, `insert!`, `DataFrames.hcat!`, `merge!`, `delete!`, `empty!`, `categorical!`, `DataFrames.index`, `permutedims!`
 6. Working with rows: `sort!`, `sort`, `issorted`, `append!`, `vcat`, `push!`, `view`, `filter`, `filter!`, `deleterows!`, `unique`, `nonunique`, `unique!`
 7. Working with categorical: `categorical`, `cut`, `isordered`, `ordered!`, `levels`, `unique`, `levels!`, `droplevels!`, `get`, `recode`, `recode!`
 8. Joining: `join`
@@ -75,7 +76,3 @@ Changelog:
 
 # Changes in DataFrames master since last update of the tutorial
 
-1. Improved rendering of `#undef` in HTML/LaTeX.
-2. Added `permutecols!` function.
-3. `describe` returns a `DataFrame`
-4. On Julia 0.7 you can access columns of `DataFrame` using `.` notation