From e94d3af3be170589697016195f1ea8faa2fa4c1f Mon Sep 17 00:00:00 2001
From: 100gle <569590461@qq.com>
Date: Thu, 30 Jun 2022 09:08:53 +0800
Subject: [PATCH] =?UTF-8?q?feat:=20=E6=96=B0=E5=A2=9EVol19=E7=AB=A0?=
 =?UTF-8?q?=E8=8A=82=E7=A4=BA=E4=BE=8B=E6=BA=90=E7=A0=81?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 code/19/pyjanitor.ipynb   | 1826 +++++++++++++++++++++++++++++++++++++
 code/19/statsmodels.ipynb |  692 ++++++++++++++
 2 files changed, 2518 insertions(+)
 create mode 100644 code/19/pyjanitor.ipynb
 create mode 100644 code/19/statsmodels.ipynb

diff --git a/code/19/pyjanitor.ipynb b/code/19/pyjanitor.ipynb
new file mode 100644
index 0000000..5246159
--- /dev/null
+++ b/code/19/pyjanitor.ipynb
@@ -0,0 +1,1826 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "# Pyjanitor"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "可以将如下代码注释后并执行安装 Pyjanitor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#!pip install pyjanitor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import janitor\n",
+    "\n",
+    "# or use `as` key word to set an alias.\n",
+    "import janitor as jn"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>a</th>\n",
+       "      <th>b231_</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>a</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>3</td>\n",
+       "      <td>b</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>c</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   a b231_\n",
+       "0  1     a\n",
+       "1  3     b\n",
+       "2  3     c"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import janitor as jn\n",
+    "import pandas as pd\n",
+    "\n",
+    "data = pd.DataFrame(\n",
+    "    {\n",
+    "        \"a\": [1, 3, 3],\n",
+    "        \"b$231@!#_\": list(\"abc\"),\n",
+    "    }\n",
+    ")\n",
+    "data.head()\n",
+    "data.pipe(jn.clean_names, remove_special=True)\n",
+    "data.clean_names(remove_special=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## coalesce"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>a</th>\n",
+       "      <th>b</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>1.3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      a     b\n",
+       "0     1  <NA>\n",
+       "1  <NA>   1.3\n",
+       "2     3  <NA>\n",
+       "3  <NA>  <NA>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# native pandas code\n",
+    "\n",
+    "import pandas as pd\n",
+    "\n",
+    "data = pd.DataFrame(\n",
+    "    {\n",
+    "        \"a\": [1, pd.NA, 3, pd.NA],\n",
+    "        \"b\": [pd.NA, 1.3, pd.NA, pd.NA],\n",
+    "    }\n",
+    ")\n",
+    "data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def use_or_not(row):\n",
+    "    a, b = pd.isna(row[\"a\"]), pd.isna(row[\"b\"])\n",
+    "    if a and not b:\n",
+    "        return row[\"b\"]\n",
+    "    elif not a and b:\n",
+    "        return row[\"a\"]\n",
+    "    else:\n",
+    "        return pd.NA"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>a</th>\n",
+       "      <th>b</th>\n",
+       "      <th>c</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>1.3</td>\n",
+       "      <td>1.3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      a     b     c\n",
+       "0     1  <NA>     1\n",
+       "1  <NA>   1.3   1.3\n",
+       "2     3  <NA>     3\n",
+       "3  <NA>  <NA>  <NA>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data[\"c\"] = data.apply(use_or_not, axis=1)\n",
+    "data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>a</th>\n",
+       "      <th>b</th>\n",
+       "      <th>c</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>1.3</td>\n",
+       "      <td>1.3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      a     b     c\n",
+       "0     1  <NA>     1\n",
+       "1  <NA>   1.3   1.3\n",
+       "2     3  <NA>     3\n",
+       "3  <NA>  <NA>  <NA>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# janitor code\n",
+    "import janitor\n",
+    "import pandas as pd\n",
+    "\n",
+    "data = pd.DataFrame(\n",
+    "    {\n",
+    "        \"a\": [1, pd.NA, 3, pd.NA],\n",
+    "        \"b\": [pd.NA, 1.3, pd.NA, pd.NA],\n",
+    "        \"c\": [3, pd.NA, 2, 3.1],\n",
+    "    }\n",
+    ")\n",
+    "data.coalesce(\"a\", \"b\", target_column_name=\"c\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>a</th>\n",
+       "      <th>b</th>\n",
+       "      <th>c</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>1.3</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>3.1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      a     b     c\n",
+       "0     1  <NA>     3\n",
+       "1  <NA>   1.3  <NA>\n",
+       "2     3  <NA>     2\n",
+       "3  <NA>  <NA>   3.1"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# DataFrame.bfill\n",
+    "import pandas as pd\n",
+    "\n",
+    "data = pd.DataFrame(\n",
+    "    {\n",
+    "        \"a\": [1, pd.NA, 3, pd.NA],\n",
+    "        \"b\": [pd.NA, 1.3, pd.NA, pd.NA],\n",
+    "        \"c\": [3, pd.NA, 2, 3.1],\n",
+    "    }\n",
+    ")\n",
+    "data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>a</th>\n",
+       "      <th>b</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1.3</td>\n",
+       "      <td>1.3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      a     b\n",
+       "0     1  <NA>\n",
+       "1   1.3   1.3\n",
+       "2     3  <NA>\n",
+       "3  <NA>  <NA>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.filter([\"a\", \"b\"]).bfill(axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>a</th>\n",
+       "      <th>b</th>\n",
+       "      <th>c</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1.3</td>\n",
+       "      <td>1.3</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3.1</td>\n",
+       "      <td>3.1</td>\n",
+       "      <td>3.1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     a    b     c\n",
+       "0  1.0  3.0     3\n",
+       "1  1.3  1.3  <NA>\n",
+       "2  3.0  2.0     2\n",
+       "3  3.1  3.1   3.1"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.filter([\"a\", \"b\", \"c\"]).bfill(axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    1.0\n",
+       "1    1.3\n",
+       "2    3.0\n",
+       "3    3.1\n",
+       "Name: a, dtype: float64"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.filter([\"a\", \"b\", \"c\"]).bfill(axis=1).iloc[:, 0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## case_when"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# native pandas code\n",
+    "import pandas as pd\n",
+    "\n",
+    "df = pd.DataFrame(\n",
+    "    {\n",
+    "        \"a\": [0, 0, 1, 2, \"hi\"],\n",
+    "        \"b\": [0, 3, 4, 5, \"bye\"],\n",
+    "        \"c\": [6, 7, 8, 9, \"wait\"],\n",
+    "    }\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def case_when(row):\n",
+    "    if (row[\"a\"] == 0 and row[\"b\"] != 0) or row[\"c\"] == \"wait\":\n",
+    "        return row[\"a\"]\n",
+    "    elif row[\"a\"] == 0 and row[\"b\"] == 0:\n",
+    "        return \"x\"\n",
+    "    else:\n",
+    "        return row[\"c\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>a</th>\n",
+       "      <th>b</th>\n",
+       "      <th>c</th>\n",
+       "      <th>new_col</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>x</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>7</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>8</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>hi</td>\n",
+       "      <td>bye</td>\n",
+       "      <td>wait</td>\n",
+       "      <td>hi</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    a    b     c new_col\n",
+       "0   0    0     6       x\n",
+       "1   0    3     7       0\n",
+       "2   1    4     8       8\n",
+       "3   2    5     9       9\n",
+       "4  hi  bye  wait      hi"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.assign(new_col=df.apply(case_when, axis=1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>a</th>\n",
+       "      <th>b</th>\n",
+       "      <th>c</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>hi</td>\n",
+       "      <td>bye</td>\n",
+       "      <td>wait</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    a    b     c\n",
+       "0   0    0     6\n",
+       "1   0    3     7\n",
+       "2   1    4     8\n",
+       "3   2    5     9\n",
+       "4  hi  bye  wait"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# janitor code\n",
+    "import janitor\n",
+    "import pandas as pd\n",
+    "\n",
+    "df = pd.DataFrame(\n",
+    "    {\n",
+    "        \"a\": [0, 0, 1, 2, \"hi\"],\n",
+    "        \"b\": [0, 3, 4, 5, \"bye\"],\n",
+    "        \"c\": [6, 7, 8, 9, \"wait\"],\n",
+    "    }\n",
+    ")\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>a</th>\n",
+       "      <th>b</th>\n",
+       "      <th>c</th>\n",
+       "      <th>new_col</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>x</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>7</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>8</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>hi</td>\n",
+       "      <td>bye</td>\n",
+       "      <td>wait</td>\n",
+       "      <td>hi</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    a    b     c new_col\n",
+       "0   0    0     6       x\n",
+       "1   0    3     7       0\n",
+       "2   1    4     8       8\n",
+       "3   2    5     9       9\n",
+       "4  hi  bye  wait      hi"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# fmt:off\n",
+    "df.case_when(\n",
+    "     ((df.a == 0) & (df.b != 0)) | (df.c == \"wait\"), df.a,\n",
+    "     (df.b == 0) & (df.a == 0), \"x\",\n",
+    "     df.c,\n",
+    "     column_name=\"new_col\",\n",
+    ")\n",
+    "# fmt:on"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## concatenate_columns & deconcatenate_column"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>no.</th>\n",
+       "      <th>prefix</th>\n",
+       "      <th>base</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>auto</td>\n",
+       "      <td>matic</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>de</td>\n",
+       "      <td>code</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>em</td>\n",
+       "      <td>body</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   no. prefix   base\n",
+       "0    1   auto  matic\n",
+       "1    2     de   code\n",
+       "2    3     em   body"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# native pandas code\n",
+    "import pandas as pd\n",
+    "\n",
+    "data = pd.DataFrame(\n",
+    "    {\n",
+    "        \"no.\": [1, 2, 3],\n",
+    "        \"prefix\": [\"auto\", \"de\", \"em\"],\n",
+    "        \"base\": [\"matic\", \"code\", \"body\"],\n",
+    "    }\n",
+    ")\n",
+    "\n",
+    "data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    auto-matic\n",
+       "1       de-code\n",
+       "2       em-body\n",
+       "Name: prefix, dtype: object"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data[\"prefix\"].str.cat(data[\"base\"], sep=\"-\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    auto-matic\n",
+       "1       de-code\n",
+       "2       em-body\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data[\"prefix\"] + \"-\" + data[\"base\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    1-auto-matic\n",
+       "1       2-de-code\n",
+       "2       3-em-body\n",
+       "Name: no., dtype: object"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(\n",
+    "    data[\"no.\"]\n",
+    "    .astype(str)\n",
+    "    .str.cat(data[\"prefix\"], sep=\"-\")\n",
+    "    .str.cat(data[\"base\"], sep=\"-\")\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>no.</th>\n",
+       "      <th>prefix</th>\n",
+       "      <th>base</th>\n",
+       "      <th>word</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>auto</td>\n",
+       "      <td>matic</td>\n",
+       "      <td>1-auto-matic</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>de</td>\n",
+       "      <td>code</td>\n",
+       "      <td>2-de-code</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>em</td>\n",
+       "      <td>body</td>\n",
+       "      <td>3-em-body</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   no. prefix   base          word\n",
+       "0    1   auto  matic  1-auto-matic\n",
+       "1    2     de   code     2-de-code\n",
+       "2    3     em   body     3-em-body"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# janitor code\n",
+    "import janitor\n",
+    "import pandas as pd\n",
+    "\n",
+    "data = pd.DataFrame(\n",
+    "    {\n",
+    "        \"no.\": [1, 2, 3],\n",
+    "        \"prefix\": [\"auto\", \"de\", \"em\"],\n",
+    "        \"base\": [\"matic\", \"code\", \"body\"],\n",
+    "    }\n",
+    ")\n",
+    "data.concatenate_columns(\n",
+    "    column_names=[\"no.\", \"prefix\", \"base\"],\n",
+    "    new_column_name=\"word\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date</th>\n",
+       "      <th>year</th>\n",
+       "      <th>month</th>\n",
+       "      <th>day</th>\n",
+       "      <th>year_month</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2022-01-02</td>\n",
+       "      <td>2022</td>\n",
+       "      <td>01</td>\n",
+       "      <td>02</td>\n",
+       "      <td>202201</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2022-01-09</td>\n",
+       "      <td>2022</td>\n",
+       "      <td>01</td>\n",
+       "      <td>09</td>\n",
+       "      <td>202201</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2022-01-16</td>\n",
+       "      <td>2022</td>\n",
+       "      <td>01</td>\n",
+       "      <td>16</td>\n",
+       "      <td>202201</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2022-01-23</td>\n",
+       "      <td>2022</td>\n",
+       "      <td>01</td>\n",
+       "      <td>23</td>\n",
+       "      <td>202201</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2022-01-30</td>\n",
+       "      <td>2022</td>\n",
+       "      <td>01</td>\n",
+       "      <td>30</td>\n",
+       "      <td>202201</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         date  year month day year_month\n",
+       "0  2022-01-02  2022    01  02     202201\n",
+       "1  2022-01-09  2022    01  09     202201\n",
+       "2  2022-01-16  2022    01  16     202201\n",
+       "3  2022-01-23  2022    01  23     202201\n",
+       "4  2022-01-30  2022    01  30     202201"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import janitor\n",
+    "import pandas as pd\n",
+    "(\n",
+    "    pd.DataFrame({\"date\": pd.date_range(\"20220101\", \"20220201\", freq=\"1W\")})\n",
+    "    .astype(str)\n",
+    "    .deconcatenate_column(\"date\", new_column_names=[\"year\", \"month\", \"day\"], sep=\"-\")\n",
+    "    .assign(year_month=lambda df: df[\"year\"].str.cat(df[\"month\"], sep=\"\"))\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## join_apply"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>a</th>\n",
+       "      <th>b</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   a  b\n",
+       "0  1  2\n",
+       "1  3  4\n",
+       "2  5  6"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# native pandas code\n",
+    "import pandas as pd\n",
+    "\n",
+    "data = pd.DataFrame(\n",
+    "    {\n",
+    "        \"a\": [1, 3, 5],\n",
+    "        \"b\": [2, 4, 6],\n",
+    "    }\n",
+    ")\n",
+    "data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>a</th>\n",
+       "      <th>b</th>\n",
+       "      <th>c</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.333333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "      <td>3.333333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5</td>\n",
+       "      <td>6</td>\n",
+       "      <td>5.333333</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   a  b         c\n",
+       "0  1  2  1.333333\n",
+       "1  3  4  3.333333\n",
+       "2  5  6  5.333333"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.assign(c=lambda df: df.apply(lambda row: (row[\"a\"] * 2 + row[\"b\"]) / 3, axis=1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>a</th>\n",
+       "      <th>b</th>\n",
+       "      <th>c</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.333333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "      <td>3.333333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5</td>\n",
+       "      <td>6</td>\n",
+       "      <td>5.333333</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   a  b         c\n",
+       "0  1  2  1.333333\n",
+       "1  3  4  3.333333\n",
+       "2  5  6  5.333333"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# equal this:\n",
+    "data.assign(\n",
+    "    c=(data[\"a\"]*2+data[\"b\"])/3\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>a</th>\n",
+       "      <th>b</th>\n",
+       "      <th>c</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.333333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "      <td>3.333333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5</td>\n",
+       "      <td>6</td>\n",
+       "      <td>5.333333</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   a  b         c\n",
+       "0  1  2  1.333333\n",
+       "1  3  4  3.333333\n",
+       "2  5  6  5.333333"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# janitor code\n",
+    "import janitor\n",
+    "import pandas as pd\n",
+    "\n",
+    "data = pd.DataFrame(\n",
+    "    {\n",
+    "        \"a\": [1, 3, 5],\n",
+    "        \"b\": [2, 4, 6],\n",
+    "    }\n",
+    ")\n",
+    "\n",
+    "data.join_apply(lambda row: (row[\"a\"] * 2 + row[\"b\"]) / 3, new_column_name=\"c\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.10.4 ('sspai-100-hours-series-python')",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.4"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "7a101baf08afe636412f97dd4a9fc2e65b6f84f0ec50413bf3e19b04a26b8ba6"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/code/19/statsmodels.ipynb b/code/19/statsmodels.ipynb
new file mode 100644
index 0000000..649b1ab
--- /dev/null
+++ b/code/19/statsmodels.ipynb
@@ -0,0 +1,692 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "%config InlineBackend.figure_format = 'svg'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import statsmodels.api as sm\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "plt.rc(\"figure\", figsize=(16, 8))\n",
+    "plt.rc(\"font\", size=14)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "data = sm.datasets.statecrime.load_pandas()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>violent</th>\n",
+       "      <th>murder</th>\n",
+       "      <th>hs_grad</th>\n",
+       "      <th>poverty</th>\n",
+       "      <th>single</th>\n",
+       "      <th>white</th>\n",
+       "      <th>urban</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>state</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Alabama</th>\n",
+       "      <td>459.9</td>\n",
+       "      <td>7.1</td>\n",
+       "      <td>82.1</td>\n",
+       "      <td>17.5</td>\n",
+       "      <td>29.0</td>\n",
+       "      <td>70.0</td>\n",
+       "      <td>48.65</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Alaska</th>\n",
+       "      <td>632.6</td>\n",
+       "      <td>3.2</td>\n",
+       "      <td>91.4</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>25.5</td>\n",
+       "      <td>68.3</td>\n",
+       "      <td>44.46</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Arizona</th>\n",
+       "      <td>423.2</td>\n",
+       "      <td>5.5</td>\n",
+       "      <td>84.2</td>\n",
+       "      <td>16.5</td>\n",
+       "      <td>25.7</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>80.07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Arkansas</th>\n",
+       "      <td>530.3</td>\n",
+       "      <td>6.3</td>\n",
+       "      <td>82.4</td>\n",
+       "      <td>18.8</td>\n",
+       "      <td>26.3</td>\n",
+       "      <td>78.4</td>\n",
+       "      <td>39.54</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>California</th>\n",
+       "      <td>473.4</td>\n",
+       "      <td>5.4</td>\n",
+       "      <td>80.6</td>\n",
+       "      <td>14.2</td>\n",
+       "      <td>27.8</td>\n",
+       "      <td>62.7</td>\n",
+       "      <td>89.73</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            violent  murder  hs_grad  poverty  single  white  urban\n",
+       "state                                                              \n",
+       "Alabama       459.9     7.1     82.1     17.5    29.0   70.0  48.65\n",
+       "Alaska        632.6     3.2     91.4      9.0    25.5   68.3  44.46\n",
+       "Arizona       423.2     5.5     84.2     16.5    25.7   80.0  80.07\n",
+       "Arkansas      530.3     6.3     82.4     18.8    26.3   78.4  39.54\n",
+       "California    473.4     5.4     80.6     14.2    27.8   62.7  89.73"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Index: 51 entries, Alabama to Wyoming\n",
+      "Data columns (total 7 columns):\n",
+      " #   Column   Non-Null Count  Dtype  \n",
+      "---  ------   --------------  -----  \n",
+      " 0   violent  51 non-null     float64\n",
+      " 1   murder   51 non-null     float64\n",
+      " 2   hs_grad  51 non-null     float64\n",
+      " 3   poverty  51 non-null     float64\n",
+      " 4   single   51 non-null     float64\n",
+      " 5   white    51 non-null     float64\n",
+      " 6   urban    51 non-null     float64\n",
+      "dtypes: float64(7)\n",
+      "memory usage: 3.2+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "data.data.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>urban</th>\n",
+       "      <th>poverty</th>\n",
+       "      <th>hs_grad</th>\n",
+       "      <th>single</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>state</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Alabama</th>\n",
+       "      <td>48.65</td>\n",
+       "      <td>17.5</td>\n",
+       "      <td>82.1</td>\n",
+       "      <td>29.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Alaska</th>\n",
+       "      <td>44.46</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>91.4</td>\n",
+       "      <td>25.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Arizona</th>\n",
+       "      <td>80.07</td>\n",
+       "      <td>16.5</td>\n",
+       "      <td>84.2</td>\n",
+       "      <td>25.7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Arkansas</th>\n",
+       "      <td>39.54</td>\n",
+       "      <td>18.8</td>\n",
+       "      <td>82.4</td>\n",
+       "      <td>26.3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>California</th>\n",
+       "      <td>89.73</td>\n",
+       "      <td>14.2</td>\n",
+       "      <td>80.6</td>\n",
+       "      <td>27.8</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            urban  poverty  hs_grad  single\n",
+       "state                                      \n",
+       "Alabama     48.65     17.5     82.1    29.0\n",
+       "Alaska      44.46      9.0     91.4    25.5\n",
+       "Arizona     80.07     16.5     84.2    25.7\n",
+       "Arkansas    39.54     18.8     82.4    26.3\n",
+       "California  89.73     14.2     80.6    27.8"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.exog.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "state\n",
+       "Alabama       7.1\n",
+       "Alaska        3.2\n",
+       "Arizona       5.5\n",
+       "Arkansas      6.3\n",
+       "California    5.4\n",
+       "Name: murder, dtype: float64"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.endog.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>const</th>\n",
+       "      <th>urban</th>\n",
+       "      <th>poverty</th>\n",
+       "      <th>hs_grad</th>\n",
+       "      <th>single</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>state</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Alabama</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>48.65</td>\n",
+       "      <td>17.5</td>\n",
+       "      <td>82.1</td>\n",
+       "      <td>29.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Alaska</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>44.46</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>91.4</td>\n",
+       "      <td>25.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Arizona</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>80.07</td>\n",
+       "      <td>16.5</td>\n",
+       "      <td>84.2</td>\n",
+       "      <td>25.7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Arkansas</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>39.54</td>\n",
+       "      <td>18.8</td>\n",
+       "      <td>82.4</td>\n",
+       "      <td>26.3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>California</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>89.73</td>\n",
+       "      <td>14.2</td>\n",
+       "      <td>80.6</td>\n",
+       "      <td>27.8</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            const  urban  poverty  hs_grad  single\n",
+       "state                                             \n",
+       "Alabama       1.0  48.65     17.5     82.1    29.0\n",
+       "Alaska        1.0  44.46      9.0     91.4    25.5\n",
+       "Arizona       1.0  80.07     16.5     84.2    25.7\n",
+       "Arkansas      1.0  39.54     18.8     82.4    26.3\n",
+       "California    1.0  89.73     14.2     80.6    27.8"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X = data.exog\n",
+    "X = sm.add_constant(X)\n",
+    "X.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "Y = data.endog"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "crime_model = sm.OLS(Y, X).fit()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# equal to this:\n",
+    "data_copy = data.data.copy()\n",
+    "data_copy = sm.add_constant(data_copy)\n",
+    "crime_model = sm.formula.ols(\n",
+    "    \"murder ~ urban + poverty + hs_grad + single + C(const)\",\n",
+    "    data=data_copy\n",
+    ").fit()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "                            OLS Regression Results                            \n",
+      "==============================================================================\n",
+      "Dep. Variable:                 murder   R-squared:                       0.813\n",
+      "Model:                            OLS   Adj. R-squared:                  0.797\n",
+      "Method:                 Least Squares   F-statistic:                     50.08\n",
+      "Date:                Thu, 30 Jun 2022   Prob (F-statistic):           3.42e-16\n",
+      "Time:                        09:07:46   Log-Likelihood:                -95.050\n",
+      "No. Observations:                  51   AIC:                             200.1\n",
+      "Df Residuals:                      46   BIC:                             209.8\n",
+      "Df Model:                           4                                         \n",
+      "Covariance Type:            nonrobust                                         \n",
+      "==============================================================================\n",
+      "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
+      "------------------------------------------------------------------------------\n",
+      "Intercept    -44.1024     12.086     -3.649      0.001     -68.430     -19.774\n",
+      "urban          0.0109      0.015      0.707      0.483      -0.020       0.042\n",
+      "poverty        0.4121      0.140      2.939      0.005       0.130       0.694\n",
+      "hs_grad        0.3059      0.117      2.611      0.012       0.070       0.542\n",
+      "single         0.6374      0.070      9.065      0.000       0.496       0.779\n",
+      "==============================================================================\n",
+      "Omnibus:                        1.618   Durbin-Watson:                   2.507\n",
+      "Prob(Omnibus):                  0.445   Jarque-Bera (JB):                0.831\n",
+      "Skew:                          -0.220   Prob(JB):                        0.660\n",
+      "Kurtosis:                       3.445   Cond. No.                     5.80e+03\n",
+      "==============================================================================\n",
+      "\n",
+      "Notes:\n",
+      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
+      "[2] The condition number is large, 5.8e+03. This might indicate that there are\n",
+      "strong multicollinearity or other numerical problems.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(crime_model.summary())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.8132403052312949\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(crime_model.rsquared)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Intercept   -44.102416\n",
+      "urban         0.010888\n",
+      "poverty       0.412150\n",
+      "hs_grad       0.305927\n",
+      "single        0.637375\n",
+      "dtype: float64\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(crime_model.params)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "eval_env: 1\n",
+      "eval_env: 1\n",
+      "eval_env: 1\n",
+      "eval_env: 1\n",
+      "eval_env: 1\n"
+     ]
+    },
+    {
+     "data": {
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+      "text/plain": [
+       "<Figure size 1152x576 with 5 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = sm.graphics.plot_partregress_grid(crime_model)\n",
+    "fig.tight_layout(pad=1.0)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
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+      "text/plain": [
+       "<Figure size 1152x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = sm.graphics.plot_fit(crime_model, \"single\")\n",
+    "fig.tight_layout(pad=1.0)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.10.4 ('sspai-100-hours-series-python')",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
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+   "file_extension": ".py",
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+  "vscode": {
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+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}