diff --git a/code/17/groupby.ipynb b/code/17/groupby.ipynb
new file mode 100644
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--- /dev/null
+++ b/code/17/groupby.ipynb
@@ -0,0 +1,2032 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "%config InlineBackend.figure_formats = ['svg']\n",
+    "\n",
+    "import random\n",
+    "\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "# GroupBy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "size\n",
+       "M       97\n",
+       "XL      90\n",
+       "XL      32\n",
+       "M       77\n",
+       "XL      39\n",
+       "Name: number, dtype: int64"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "random.seed(233)\n",
+    "\n",
+    "number = [random.randint(10, 100) for _ in range(10)]\n",
+    "size = [random.choices([\"M\", \"L\", \"XL\"], k=10)]\n",
+    "\n",
+    "s = pd.Series(number, index=size, name=\"number\").rename_axis(\"size\")\n",
+    "s.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "size\n",
+       "L      23\n",
+       "M     230\n",
+       "XL    312\n",
+       "Name: number, dtype: int64"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s.groupby(level=0).sum()"
+   ]
+  },
+  {
+   "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>size</th>\n",
+       "      <th>number</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>M</td>\n",
+       "      <td>97</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>XL</td>\n",
+       "      <td>90</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>XL</td>\n",
+       "      <td>32</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>M</td>\n",
+       "      <td>77</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>XL</td>\n",
+       "      <td>39</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  size  number\n",
+       "0    M      97\n",
+       "1   XL      90\n",
+       "2   XL      32\n",
+       "3    M      77\n",
+       "4   XL      39"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = s.to_frame().reset_index()\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "size\n",
+       "L      23\n",
+       "M     230\n",
+       "XL    312\n",
+       "Name: number, dtype: int64"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.groupby(\"size\")[\"number\"].sum()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "### GroupBy 的一些使用场景"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/var/folders/0t/s0c95rbs6ds7w_b0d471p0kc0000gn/T/ipykernel_9426/460248279.py:2: FutureWarning: The default value of regex will change from True to False in a future version. In addition, single character regular expressions will *not* be treated as literal strings when regex=True.\n",
+      "  iris.columns = iris.columns.str.replace(\".\", \"_\")\n"
+     ]
+    }
+   ],
+   "source": [
+    "iris = pd.read_csv(\"../../data/iris.csv\")\n",
+    "iris.columns = iris.columns.str.replace(\".\", \"_\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 150 entries, 0 to 149\n",
+      "Data columns (total 5 columns):\n",
+      " #   Column        Non-Null Count  Dtype  \n",
+      "---  ------        --------------  -----  \n",
+      " 0   sepal_length  150 non-null    float64\n",
+      " 1   sepal_width   150 non-null    float64\n",
+      " 2   petal_length  150 non-null    float64\n",
+      " 3   petal_width   150 non-null    float64\n",
+      " 4   variety       150 non-null    object \n",
+      "dtypes: float64(4), object(1)\n",
+      "memory usage: 6.0+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "iris.info()"
+   ]
+  },
+  {
+   "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>sepal_length</th>\n",
+       "      <th>sepal_width</th>\n",
+       "      <th>petal_length</th>\n",
+       "      <th>petal_width</th>\n",
+       "      <th>variety</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>5.1</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>Setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>4.9</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>Setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>4.7</td>\n",
+       "      <td>3.2</td>\n",
+       "      <td>1.3</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>Setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4.6</td>\n",
+       "      <td>3.1</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>Setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5.0</td>\n",
+       "      <td>3.6</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>Setosa</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   sepal_length  sepal_width  petal_length  petal_width variety\n",
+       "0           5.1          3.5           1.4          0.2  Setosa\n",
+       "1           4.9          3.0           1.4          0.2  Setosa\n",
+       "2           4.7          3.2           1.3          0.2  Setosa\n",
+       "3           4.6          3.1           1.5          0.2  Setosa\n",
+       "4           5.0          3.6           1.4          0.2  Setosa"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "iris.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "#### 自定义函数"
+   ]
+  },
+  {
+   "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>variety</th>\n",
+       "      <th>weight</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Setosa</td>\n",
+       "      <td>32.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Setosa</td>\n",
+       "      <td>7.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Setosa</td>\n",
+       "      <td>15.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Setosa</td>\n",
+       "      <td>8.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Setosa</td>\n",
+       "      <td>36.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>145</th>\n",
+       "      <td>Virginica</td>\n",
+       "      <td>26.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>146</th>\n",
+       "      <td>Virginica</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>147</th>\n",
+       "      <td>Virginica</td>\n",
+       "      <td>23.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>148</th>\n",
+       "      <td>Virginica</td>\n",
+       "      <td>43.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>149</th>\n",
+       "      <td>Virginica</td>\n",
+       "      <td>18.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>150 rows × 2 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       variety  weight\n",
+       "0       Setosa    32.5\n",
+       "1       Setosa     7.0\n",
+       "2       Setosa    15.5\n",
+       "3       Setosa     8.5\n",
+       "4       Setosa    36.0\n",
+       "..         ...     ...\n",
+       "145  Virginica    26.0\n",
+       "146  Virginica     4.0\n",
+       "147  Virginica    23.0\n",
+       "148  Virginica    43.0\n",
+       "149  Virginica    18.0\n",
+       "\n",
+       "[150 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def rank_by_sepal(group):\n",
+    "    df = group.copy()\n",
+    "    df[\"weight\"] = 0.8*df[\"sepal_width\"] + 0.2*df[\"sepal_length\"]\n",
+    "    return df[\"weight\"].rank()\n",
+    "\n",
+    "\n",
+    "iris.groupby(\"variety\").apply(rank_by_sepal).reset_index(level=0)"
+   ]
+  },
+  {
+   "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>variety</th>\n",
+       "      <th>weight</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Setosa</td>\n",
+       "      <td>32.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Setosa</td>\n",
+       "      <td>7.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Setosa</td>\n",
+       "      <td>15.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Setosa</td>\n",
+       "      <td>8.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Setosa</td>\n",
+       "      <td>36.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>145</th>\n",
+       "      <td>Virginica</td>\n",
+       "      <td>26.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>146</th>\n",
+       "      <td>Virginica</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>147</th>\n",
+       "      <td>Virginica</td>\n",
+       "      <td>23.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>148</th>\n",
+       "      <td>Virginica</td>\n",
+       "      <td>43.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>149</th>\n",
+       "      <td>Virginica</td>\n",
+       "      <td>18.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>150 rows × 2 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       variety  weight\n",
+       "0       Setosa    32.5\n",
+       "1       Setosa     7.0\n",
+       "2       Setosa    15.5\n",
+       "3       Setosa     8.5\n",
+       "4       Setosa    36.0\n",
+       "..         ...     ...\n",
+       "145  Virginica    26.0\n",
+       "146  Virginica     4.0\n",
+       "147  Virginica    23.0\n",
+       "148  Virginica    43.0\n",
+       "149  Virginica    18.0\n",
+       "\n",
+       "[150 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "iris.groupby(\"variety\").apply(lambda grp: rank_by_sepal(grp)).reset_index(level=0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "#### 分组排序求前 TOP N"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "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></th>\n",
+       "      <th>sepal_length</th>\n",
+       "      <th>sepal_width</th>\n",
+       "      <th>petal_length</th>\n",
+       "      <th>petal_width</th>\n",
+       "      <th>variety</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>variety</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 rowspan=\"2\" valign=\"top\">Setosa</th>\n",
+       "      <th>14</th>\n",
+       "      <td>5.8</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.2</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>Setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>5.7</td>\n",
+       "      <td>4.4</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>0.4</td>\n",
+       "      <td>Setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"2\" valign=\"top\">Versicolor</th>\n",
+       "      <th>50</th>\n",
+       "      <td>7.0</td>\n",
+       "      <td>3.2</td>\n",
+       "      <td>4.7</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>Versicolor</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>6.9</td>\n",
+       "      <td>3.1</td>\n",
+       "      <td>4.9</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>Versicolor</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"2\" valign=\"top\">Virginica</th>\n",
+       "      <th>131</th>\n",
+       "      <td>7.9</td>\n",
+       "      <td>3.8</td>\n",
+       "      <td>6.4</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>Virginica</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>117</th>\n",
+       "      <td>7.7</td>\n",
+       "      <td>3.8</td>\n",
+       "      <td>6.7</td>\n",
+       "      <td>2.2</td>\n",
+       "      <td>Virginica</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                sepal_length  sepal_width  petal_length  petal_width  \\\n",
+       "variety                                                                \n",
+       "Setosa     14            5.8          4.0           1.2          0.2   \n",
+       "           15            5.7          4.4           1.5          0.4   \n",
+       "Versicolor 50            7.0          3.2           4.7          1.4   \n",
+       "           52            6.9          3.1           4.9          1.5   \n",
+       "Virginica  131           7.9          3.8           6.4          2.0   \n",
+       "           117           7.7          3.8           6.7          2.2   \n",
+       "\n",
+       "                   variety  \n",
+       "variety                     \n",
+       "Setosa     14       Setosa  \n",
+       "           15       Setosa  \n",
+       "Versicolor 50   Versicolor  \n",
+       "           52   Versicolor  \n",
+       "Virginica  131   Virginica  \n",
+       "           117   Virginica  "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "iris.groupby(\"variety\").apply(\n",
+    "    lambda grp: grp.sort_values([\"sepal_length\", \"sepal_width\"], ascending=False)\n",
+    "        .head(2),\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "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>sepal_length</th>\n",
+       "      <th>sepal_width</th>\n",
+       "      <th>petal_length</th>\n",
+       "      <th>petal_width</th>\n",
+       "      <th>variety</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>5.1</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>Setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>4.9</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>Setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>7.0</td>\n",
+       "      <td>3.2</td>\n",
+       "      <td>4.7</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>Versicolor</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>6.4</td>\n",
+       "      <td>3.2</td>\n",
+       "      <td>4.5</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>Versicolor</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>100</th>\n",
+       "      <td>6.3</td>\n",
+       "      <td>3.3</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>2.5</td>\n",
+       "      <td>Virginica</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>101</th>\n",
+       "      <td>5.8</td>\n",
+       "      <td>2.7</td>\n",
+       "      <td>5.1</td>\n",
+       "      <td>1.9</td>\n",
+       "      <td>Virginica</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     sepal_length  sepal_width  petal_length  petal_width     variety\n",
+       "0             5.1          3.5           1.4          0.2      Setosa\n",
+       "1             4.9          3.0           1.4          0.2      Setosa\n",
+       "50            7.0          3.2           4.7          1.4  Versicolor\n",
+       "51            6.4          3.2           4.5          1.5  Versicolor\n",
+       "100           6.3          3.3           6.0          2.5   Virginica\n",
+       "101           5.8          2.7           5.1          1.9   Virginica"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "iris.groupby(\"variety\").head(2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "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>sepal_length</th>\n",
+       "      <th>sepal_width</th>\n",
+       "      <th>petal_length</th>\n",
+       "      <th>petal_width</th>\n",
+       "      <th>variety</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>5.0</td>\n",
+       "      <td>3.3</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>Setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>99</th>\n",
+       "      <td>5.7</td>\n",
+       "      <td>2.8</td>\n",
+       "      <td>4.1</td>\n",
+       "      <td>1.3</td>\n",
+       "      <td>Versicolor</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>149</th>\n",
+       "      <td>5.9</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>5.1</td>\n",
+       "      <td>1.8</td>\n",
+       "      <td>Virginica</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     sepal_length  sepal_width  petal_length  petal_width     variety\n",
+       "49            5.0          3.3           1.4          0.2      Setosa\n",
+       "99            5.7          2.8           4.1          1.3  Versicolor\n",
+       "149           5.9          3.0           5.1          1.8   Virginica"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "iris.groupby(\"variety\").tail(1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "#### 分组聚合"
+   ]
+  },
+  {
+   "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>sepal_length</th>\n",
+       "      <th>sepal_width</th>\n",
+       "      <th>petal_length</th>\n",
+       "      <th>petal_width</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>variety</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Setosa</th>\n",
+       "      <td>0.266674</td>\n",
+       "      <td>0.189941</td>\n",
+       "      <td>-0.357011</td>\n",
+       "      <td>-0.436492</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Setosa</th>\n",
+       "      <td>-0.300718</td>\n",
+       "      <td>-1.129096</td>\n",
+       "      <td>-0.357011</td>\n",
+       "      <td>-0.436492</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Setosa</th>\n",
+       "      <td>-0.868111</td>\n",
+       "      <td>-0.601481</td>\n",
+       "      <td>-0.932836</td>\n",
+       "      <td>-0.436492</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Setosa</th>\n",
+       "      <td>-1.151807</td>\n",
+       "      <td>-0.865288</td>\n",
+       "      <td>0.218813</td>\n",
+       "      <td>-0.436492</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Setosa</th>\n",
+       "      <td>-0.017022</td>\n",
+       "      <td>0.453749</td>\n",
+       "      <td>-0.357011</td>\n",
+       "      <td>-0.436492</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Virginica</th>\n",
+       "      <td>0.176134</td>\n",
+       "      <td>0.080621</td>\n",
+       "      <td>-0.637803</td>\n",
+       "      <td>0.997633</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Virginica</th>\n",
+       "      <td>-0.452916</td>\n",
+       "      <td>-1.469783</td>\n",
+       "      <td>-1.000191</td>\n",
+       "      <td>-0.458766</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Virginica</th>\n",
+       "      <td>-0.138391</td>\n",
+       "      <td>0.080621</td>\n",
+       "      <td>-0.637803</td>\n",
+       "      <td>-0.094666</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Virginica</th>\n",
+       "      <td>-0.610178</td>\n",
+       "      <td>1.320944</td>\n",
+       "      <td>-0.275415</td>\n",
+       "      <td>0.997633</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Virginica</th>\n",
+       "      <td>-1.081966</td>\n",
+       "      <td>0.080621</td>\n",
+       "      <td>-0.818997</td>\n",
+       "      <td>-0.822865</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>150 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           sepal_length  sepal_width  petal_length  petal_width\n",
+       "variety                                                        \n",
+       "Setosa         0.266674     0.189941     -0.357011    -0.436492\n",
+       "Setosa        -0.300718    -1.129096     -0.357011    -0.436492\n",
+       "Setosa        -0.868111    -0.601481     -0.932836    -0.436492\n",
+       "Setosa        -1.151807    -0.865288      0.218813    -0.436492\n",
+       "Setosa        -0.017022     0.453749     -0.357011    -0.436492\n",
+       "...                 ...          ...           ...          ...\n",
+       "Virginica      0.176134     0.080621     -0.637803     0.997633\n",
+       "Virginica     -0.452916    -1.469783     -1.000191    -0.458766\n",
+       "Virginica     -0.138391     0.080621     -0.637803    -0.094666\n",
+       "Virginica     -0.610178     1.320944     -0.275415     0.997633\n",
+       "Virginica     -1.081966     0.080621     -0.818997    -0.822865\n",
+       "\n",
+       "[150 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "normalize = lambda x: (x - x.mean()) / x.std()\n",
+    "\n",
+    "iris.set_index(\"variety\").groupby(level=0).transform(normalize)"
+   ]
+  },
+  {
+   "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>count</th>\n",
+       "      <th>min</th>\n",
+       "      <th>std</th>\n",
+       "      <th>max</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>variety</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Setosa</th>\n",
+       "      <td>50</td>\n",
+       "      <td>4.3</td>\n",
+       "      <td>0.352490</td>\n",
+       "      <td>5.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Versicolor</th>\n",
+       "      <td>50</td>\n",
+       "      <td>4.9</td>\n",
+       "      <td>0.516171</td>\n",
+       "      <td>7.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Virginica</th>\n",
+       "      <td>50</td>\n",
+       "      <td>4.9</td>\n",
+       "      <td>0.635880</td>\n",
+       "      <td>7.9</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            count  min       std  max\n",
+       "variety                              \n",
+       "Setosa         50  4.3  0.352490  5.8\n",
+       "Versicolor     50  4.9  0.516171  7.0\n",
+       "Virginica      50  4.9  0.635880  7.9"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "iris.groupby(\"variety\").agg(\n",
+    "    count = (\"variety\", \"count\"),\n",
+    "    min = (\"sepal_length\", min),\n",
+    "    std = (\"sepal_length\", \"std\"),\n",
+    "    max = (\"sepal_length\", max),\n",
+    ")"
+   ]
+  },
+  {
+   "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>count</th>\n",
+       "      <th>min</th>\n",
+       "      <th>std</th>\n",
+       "      <th>max</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Setosa</th>\n",
+       "      <td>50</td>\n",
+       "      <td>4.3</td>\n",
+       "      <td>0.352490</td>\n",
+       "      <td>5.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Versicolor</th>\n",
+       "      <td>50</td>\n",
+       "      <td>4.9</td>\n",
+       "      <td>0.516171</td>\n",
+       "      <td>7.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Virginica</th>\n",
+       "      <td>50</td>\n",
+       "      <td>4.9</td>\n",
+       "      <td>0.635880</td>\n",
+       "      <td>7.9</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            count  min       std  max\n",
+       "Setosa         50  4.3  0.352490  5.8\n",
+       "Versicolor     50  4.9  0.516171  7.0\n",
+       "Virginica      50  4.9  0.635880  7.9"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# equal to:\n",
+    "\n",
+    "data = []\n",
+    "groups = iris[\"variety\"].unique()\n",
+    "for group in groups:\n",
+    "    df = iris[iris[\"variety\"] == group]\n",
+    "    stats = pd.DataFrame(\n",
+    "        dict(\n",
+    "            count = df.shape[0],\n",
+    "            min = df[\"sepal_length\"].min(),\n",
+    "            std = df[\"sepal_length\"].std(),\n",
+    "            max = df[\"sepal_length\"].max(),\n",
+    "        ),\n",
+    "        index=[group],\n",
+    "    )\n",
+    "    data.append(stats)\n",
+    "\n",
+    "pd.concat(data)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "#### 分组绘制可视化图形"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "variety\n",
+       "Setosa        AxesSubplot(0.125,0.125;0.775x0.755)\n",
+       "Versicolor    AxesSubplot(0.125,0.125;0.775x0.755)\n",
+       "Virginica     AxesSubplot(0.125,0.125;0.775x0.755)\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
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+       "<Figure size 1152x144 with 1 Axes>"
+      ]
+     },
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+   "source": [
+    "iris.groupby(\"variety\").plot.kde(legend=True, figsize=(16, 2))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/var/folders/0t/s0c95rbs6ds7w_b0d471p0kc0000gn/T/ipykernel_9426/838838217.py:9: UserWarning: Matplotlib is currently using module://matplotlib_inline.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
+      "  fig.show()\n"
+     ]
+    },
+    {
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+      "text/plain": [
+       "<Figure size 1152x720 with 3 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(16, 10))\n",
+    "for n, (klass, grp) in enumerate(iris.groupby(\"variety\")):\n",
+    "    location = 220+n+1\n",
+    "    axes = fig.add_subplot(location)\n",
+    "\n",
+    "    grp.drop(\"variety\", axis=1).plot.box(ax=axes)\n",
+    "    axes.set_title(f\"variety={klass}\")\n",
+    "\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "# Resampler"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "DatetimeIndex: 732 entries, 2020-01-01 to 2022-01-01\n",
+      "Freq: D\n",
+      "Data columns (total 1 columns):\n",
+      " #   Column  Non-Null Count  Dtype\n",
+      "---  ------  --------------  -----\n",
+      " 0   sales   732 non-null    int64\n",
+      "dtypes: int64(1)\n",
+      "memory usage: 11.4 KB\n"
+     ]
+    },
+    {
+     "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>sales</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>datetime</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2020-01-01</th>\n",
+       "      <td>2956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-02</th>\n",
+       "      <td>8704</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-03</th>\n",
+       "      <td>3881</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-04</th>\n",
+       "      <td>8031</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-05</th>\n",
+       "      <td>9124</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            sales\n",
+       "datetime         \n",
+       "2020-01-01   2956\n",
+       "2020-01-02   8704\n",
+       "2020-01-03   3881\n",
+       "2020-01-04   8031\n",
+       "2020-01-05   9124"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "import random\n",
+    "random.seed(233)\n",
+    "\n",
+    "dt = pd.date_range(start=\"20200101\", end=\"20220101\", freq=\"D\").set_names(\"datetime\")\n",
+    "data = pd.DataFrame(\n",
+    "    [random.randrange(100, 10000) for _ in range(len(dt))],\n",
+    "    index=dt,\n",
+    "    columns=[\"sales\"],\n",
+    ")\n",
+    "data.info()\n",
+    "data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "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>sales</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>datetime</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2020-12-31</th>\n",
+       "      <td>1850914</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-12-31</th>\n",
+       "      <td>1901049</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2022-12-31</th>\n",
+       "      <td>2581</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              sales\n",
+       "datetime           \n",
+       "2020-12-31  1850914\n",
+       "2021-12-31  1901049\n",
+       "2022-12-31     2581"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.resample(\"Y\").sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<pandas.core.resample.DatetimeIndexResampler object at 0x133298a30>"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.resample(\"2W\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<pandas.core.resample.DatetimeIndexResampler object at 0x133299180>"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dt.to_series().resample(\"3M\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<pandas.core.resample.PeriodIndexResampler object at 0x133299480>"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dt.to_period(\"2W\").to_series().resample(\"3d\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# data.reset_index().resample(\"4d\")  # raise type error here."
+   ]
+  },
+  {
+   "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>datetime</th>\n",
+       "      <th>sales</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2020-01-01</td>\n",
+       "      <td>2956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2020-01-02</td>\n",
+       "      <td>8704</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2020-01-03</td>\n",
+       "      <td>3881</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2020-01-04</td>\n",
+       "      <td>8031</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2020-01-05</td>\n",
+       "      <td>9124</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    datetime  sales\n",
+       "0 2020-01-01   2956\n",
+       "1 2020-01-02   8704\n",
+       "2 2020-01-03   3881\n",
+       "3 2020-01-04   8031\n",
+       "4 2020-01-05   9124"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = data.reset_index()\n",
+    "data.head()"
+   ]
+  },
+  {
+   "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>sales</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>datetime</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2020-12-31</th>\n",
+       "      <td>1850914</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-12-31</th>\n",
+       "      <td>1901049</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2022-12-31</th>\n",
+       "      <td>2581</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              sales\n",
+       "datetime           \n",
+       "2020-12-31  1850914\n",
+       "2021-12-31  1901049\n",
+       "2022-12-31     2581"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.groupby(pd.Grouper(key=\"datetime\", freq=\"Y\")).sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
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+      "text/plain": [
+       "<Figure size 720x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "ax = plt.subplot(111)\n",
+    "\n",
+    "random.seed(233)\n",
+    "\n",
+    "(\n",
+    "    data.set_index(\"datetime\")\n",
+    "    .assign(\n",
+    "        overseas_sales = [random.randrange(1000, 5000) for _ in range(len(dt))],\n",
+    "    )\n",
+    "    .resample(\"3W\")\n",
+    "    .sum()\n",
+    "    .plot.line(\n",
+    "        figsize=(10, 5),\n",
+    "        ylabel=\"sales\",\n",
+    "        xlabel=\"\",\n",
+    "        ax=ax,\n",
+    "    )\n",
+    ")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
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+      "text/plain": [
+       "<Figure size 720x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "ax = plt.subplot(111)\n",
+    "\n",
+    "random.seed(233)\n",
+    "\n",
+    "(\n",
+    "    data.assign(\n",
+    "        overseas_sales = [\n",
+    "            random.randrange(1000, 5000) for _ in range(len(dt))\n",
+    "        ],\n",
+    "    )\n",
+    "    .groupby(pd.Grouper(key=\"datetime\", freq=\"3W\"))\n",
+    "    .sum()\n",
+    "    .plot.line(\n",
+    "        figsize=(10, 5),\n",
+    "        ylabel=\"sales\",\n",
+    "        xlabel=\"\",\n",
+    "        ax=ax,\n",
+    "    )\n",
+    ")\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",
+    "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/data/iris.csv b/data/iris.csv
new file mode 100644
index 0000000..1b9d029
--- /dev/null
+++ b/data/iris.csv
@@ -0,0 +1,151 @@
+"sepal.length","sepal.width","petal.length","petal.width","variety"
+5.1,3.5,1.4,.2,"Setosa"
+4.9,3,1.4,.2,"Setosa"
+4.7,3.2,1.3,.2,"Setosa"
+4.6,3.1,1.5,.2,"Setosa"
+5,3.6,1.4,.2,"Setosa"
+5.4,3.9,1.7,.4,"Setosa"
+4.6,3.4,1.4,.3,"Setosa"
+5,3.4,1.5,.2,"Setosa"
+4.4,2.9,1.4,.2,"Setosa"
+4.9,3.1,1.5,.1,"Setosa"
+5.4,3.7,1.5,.2,"Setosa"
+4.8,3.4,1.6,.2,"Setosa"
+4.8,3,1.4,.1,"Setosa"
+4.3,3,1.1,.1,"Setosa"
+5.8,4,1.2,.2,"Setosa"
+5.7,4.4,1.5,.4,"Setosa"
+5.4,3.9,1.3,.4,"Setosa"
+5.1,3.5,1.4,.3,"Setosa"
+5.7,3.8,1.7,.3,"Setosa"
+5.1,3.8,1.5,.3,"Setosa"
+5.4,3.4,1.7,.2,"Setosa"
+5.1,3.7,1.5,.4,"Setosa"
+4.6,3.6,1,.2,"Setosa"
+5.1,3.3,1.7,.5,"Setosa"
+4.8,3.4,1.9,.2,"Setosa"
+5,3,1.6,.2,"Setosa"
+5,3.4,1.6,.4,"Setosa"
+5.2,3.5,1.5,.2,"Setosa"
+5.2,3.4,1.4,.2,"Setosa"
+4.7,3.2,1.6,.2,"Setosa"
+4.8,3.1,1.6,.2,"Setosa"
+5.4,3.4,1.5,.4,"Setosa"
+5.2,4.1,1.5,.1,"Setosa"
+5.5,4.2,1.4,.2,"Setosa"
+4.9,3.1,1.5,.2,"Setosa"
+5,3.2,1.2,.2,"Setosa"
+5.5,3.5,1.3,.2,"Setosa"
+4.9,3.6,1.4,.1,"Setosa"
+4.4,3,1.3,.2,"Setosa"
+5.1,3.4,1.5,.2,"Setosa"
+5,3.5,1.3,.3,"Setosa"
+4.5,2.3,1.3,.3,"Setosa"
+4.4,3.2,1.3,.2,"Setosa"
+5,3.5,1.6,.6,"Setosa"
+5.1,3.8,1.9,.4,"Setosa"
+4.8,3,1.4,.3,"Setosa"
+5.1,3.8,1.6,.2,"Setosa"
+4.6,3.2,1.4,.2,"Setosa"
+5.3,3.7,1.5,.2,"Setosa"
+5,3.3,1.4,.2,"Setosa"
+7,3.2,4.7,1.4,"Versicolor"
+6.4,3.2,4.5,1.5,"Versicolor"
+6.9,3.1,4.9,1.5,"Versicolor"
+5.5,2.3,4,1.3,"Versicolor"
+6.5,2.8,4.6,1.5,"Versicolor"
+5.7,2.8,4.5,1.3,"Versicolor"
+6.3,3.3,4.7,1.6,"Versicolor"
+4.9,2.4,3.3,1,"Versicolor"
+6.6,2.9,4.6,1.3,"Versicolor"
+5.2,2.7,3.9,1.4,"Versicolor"
+5,2,3.5,1,"Versicolor"
+5.9,3,4.2,1.5,"Versicolor"
+6,2.2,4,1,"Versicolor"
+6.1,2.9,4.7,1.4,"Versicolor"
+5.6,2.9,3.6,1.3,"Versicolor"
+6.7,3.1,4.4,1.4,"Versicolor"
+5.6,3,4.5,1.5,"Versicolor"
+5.8,2.7,4.1,1,"Versicolor"
+6.2,2.2,4.5,1.5,"Versicolor"
+5.6,2.5,3.9,1.1,"Versicolor"
+5.9,3.2,4.8,1.8,"Versicolor"
+6.1,2.8,4,1.3,"Versicolor"
+6.3,2.5,4.9,1.5,"Versicolor"
+6.1,2.8,4.7,1.2,"Versicolor"
+6.4,2.9,4.3,1.3,"Versicolor"
+6.6,3,4.4,1.4,"Versicolor"
+6.8,2.8,4.8,1.4,"Versicolor"
+6.7,3,5,1.7,"Versicolor"
+6,2.9,4.5,1.5,"Versicolor"
+5.7,2.6,3.5,1,"Versicolor"
+5.5,2.4,3.8,1.1,"Versicolor"
+5.5,2.4,3.7,1,"Versicolor"
+5.8,2.7,3.9,1.2,"Versicolor"
+6,2.7,5.1,1.6,"Versicolor"
+5.4,3,4.5,1.5,"Versicolor"
+6,3.4,4.5,1.6,"Versicolor"
+6.7,3.1,4.7,1.5,"Versicolor"
+6.3,2.3,4.4,1.3,"Versicolor"
+5.6,3,4.1,1.3,"Versicolor"
+5.5,2.5,4,1.3,"Versicolor"
+5.5,2.6,4.4,1.2,"Versicolor"
+6.1,3,4.6,1.4,"Versicolor"
+5.8,2.6,4,1.2,"Versicolor"
+5,2.3,3.3,1,"Versicolor"
+5.6,2.7,4.2,1.3,"Versicolor"
+5.7,3,4.2,1.2,"Versicolor"
+5.7,2.9,4.2,1.3,"Versicolor"
+6.2,2.9,4.3,1.3,"Versicolor"
+5.1,2.5,3,1.1,"Versicolor"
+5.7,2.8,4.1,1.3,"Versicolor"
+6.3,3.3,6,2.5,"Virginica"
+5.8,2.7,5.1,1.9,"Virginica"
+7.1,3,5.9,2.1,"Virginica"
+6.3,2.9,5.6,1.8,"Virginica"
+6.5,3,5.8,2.2,"Virginica"
+7.6,3,6.6,2.1,"Virginica"
+4.9,2.5,4.5,1.7,"Virginica"
+7.3,2.9,6.3,1.8,"Virginica"
+6.7,2.5,5.8,1.8,"Virginica"
+7.2,3.6,6.1,2.5,"Virginica"
+6.5,3.2,5.1,2,"Virginica"
+6.4,2.7,5.3,1.9,"Virginica"
+6.8,3,5.5,2.1,"Virginica"
+5.7,2.5,5,2,"Virginica"
+5.8,2.8,5.1,2.4,"Virginica"
+6.4,3.2,5.3,2.3,"Virginica"
+6.5,3,5.5,1.8,"Virginica"
+7.7,3.8,6.7,2.2,"Virginica"
+7.7,2.6,6.9,2.3,"Virginica"
+6,2.2,5,1.5,"Virginica"
+6.9,3.2,5.7,2.3,"Virginica"
+5.6,2.8,4.9,2,"Virginica"
+7.7,2.8,6.7,2,"Virginica"
+6.3,2.7,4.9,1.8,"Virginica"
+6.7,3.3,5.7,2.1,"Virginica"
+7.2,3.2,6,1.8,"Virginica"
+6.2,2.8,4.8,1.8,"Virginica"
+6.1,3,4.9,1.8,"Virginica"
+6.4,2.8,5.6,2.1,"Virginica"
+7.2,3,5.8,1.6,"Virginica"
+7.4,2.8,6.1,1.9,"Virginica"
+7.9,3.8,6.4,2,"Virginica"
+6.4,2.8,5.6,2.2,"Virginica"
+6.3,2.8,5.1,1.5,"Virginica"
+6.1,2.6,5.6,1.4,"Virginica"
+7.7,3,6.1,2.3,"Virginica"
+6.3,3.4,5.6,2.4,"Virginica"
+6.4,3.1,5.5,1.8,"Virginica"
+6,3,4.8,1.8,"Virginica"
+6.9,3.1,5.4,2.1,"Virginica"
+6.7,3.1,5.6,2.4,"Virginica"
+6.9,3.1,5.1,2.3,"Virginica"
+5.8,2.7,5.1,1.9,"Virginica"
+6.8,3.2,5.9,2.3,"Virginica"
+6.7,3.3,5.7,2.5,"Virginica"
+6.7,3,5.2,2.3,"Virginica"
+6.3,2.5,5,1.9,"Virginica"
+6.5,3,5.2,2,"Virginica"
+6.2,3.4,5.4,2.3,"Virginica"
+5.9,3,5.1,1.8,"Virginica"
\ No newline at end of file