melt enhancemenet.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# melt enhancement\n",
    "\n",
    "### New features\n",
    "* Melts different groups of columns by passing a list of lists into value_vars. Each group gets melted into its own column. This feature replaces the need for `lreshape`.\n",
    "* When melting different groups of columns, groups do not have to be the same length. The shorter groups are filled with missing values.\n",
    "* Adds parameters `stubnames`(boolean), `prefix` and `sep` from function `wide_to_long`. It keeps the suffixes in separate columns and does not align them like `wide_to_long`.\n",
    "* Fixes bug when selecting a column level of a MultiIndex\n",
    "* Can select any number of MultiIndex levels\n",
    "* Works with repeated column names, which normally show up when selecting a subset of MultiIndex levels\n",
    "* Performance is ~30-40% faster than original melt, slightly slower than `lreshape` and much faster than `wide_to_long` "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How to use new melt\n",
    "Run this code block below and directly use the function `melt`. Put `pd.` in front of call to `melt` to use current pandas version."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas.core.dtypes.common import is_list_like\n",
    "from pandas.core.frame import DataFrame\n",
    "from pandas.core.index import MultiIndex\n",
    "from pandas import compat\n",
    "from IPython.display import display\n",
    "from pandas.core.reshape.concat import concat\n",
    "import re\n",
    "from pandas.core.tools.numeric import to_numeric\n",
    "from pandas.util._decorators import Appender\n",
    "from pandas.core.frame import _shared_docs\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pandas.util.testing as tm\n",
    "\n",
    "\n",
    "def _melt(frame, id_vars=None, value_vars=None, var_name=None,\n",
    "          value_name='value', col_level=None, stubnames=False,\n",
    "          suffix=r'\\d+', sep='', extra_group=0, var_end=None):\n",
    "    # TODO: what about the existing index?\n",
    "\n",
    "    def check_vars(frame, var, var_string):\n",
    "        for v in var:\n",
    "            if num_col_levels > 1:\n",
    "                if not isinstance(v, tuple):\n",
    "                    raise ValueError('{} must be a list of tuples'\n",
    "                                     ' when columns are a MultiIndex'\n",
    "                                     .format(var_string))\n",
    "                elif len(v) != num_col_levels:\n",
    "                    raise ValueError('all tuples in {} must be length {}'\n",
    "                                     .format(var_string,\n",
    "                                             frame.columns.nlevels))\n",
    "            else:\n",
    "                if is_list_like(v) and len(v) > 1:\n",
    "                    raise ValueError('DataFrame has only a single level of '\n",
    "                                     'columns. {} is not a column'.format(v))\n",
    "\n",
    "    if len(col_level) == 0:\n",
    "        num_col_levels = frame.columns.nlevels\n",
    "    else:\n",
    "        num_col_levels = len(col_level)\n",
    "\n",
    "    check_vars(frame, id_vars, 'id_vars')\n",
    "    check_vars(frame, value_vars, 'value_vars')\n",
    "\n",
    "    if var_name != [] and len(var_name) != num_col_levels:\n",
    "        raise ValueError('Length of var_name must match effective number of '\n",
    "                         'column levels.')\n",
    "    \n",
    "    if col_level != []:\n",
    "        droplevels = list(range(frame.columns.nlevels))\n",
    "        for level in col_level:\n",
    "            if isinstance(level, int):\n",
    "                droplevels.remove(level)\n",
    "            else:\n",
    "                droplevels.remove(frame.columns.names.index(level))\n",
    "        if droplevels != []:\n",
    "            frame = frame.copy()\n",
    "            frame.columns = frame.columns.droplevel(droplevels)\n",
    "\n",
    "    if stubnames and isinstance(frame.columns, MultiIndex):\n",
    "        raise ValueError('Stubnames only work with single-index DataFrames')\n",
    "        \n",
    "    for iv in id_vars:\n",
    "        if iv not in frame.columns:\n",
    "            raise KeyError('{} not in columns'.format(iv))\n",
    "\n",
    "    if value_vars != []:\n",
    "        for vv in value_vars:\n",
    "            if vv not in frame.columns:\n",
    "                raise KeyError('{} not in columns'.format(vv))\n",
    "                \n",
    "    if var_name == []:\n",
    "        names = list(frame.columns.names)\n",
    "        if len(names) == 1:\n",
    "            if names[0] is None:\n",
    "                var_name.append('variable')\n",
    "            else:\n",
    "                var_name.append(names[0])\n",
    "        elif names.count(None) == 1:\n",
    "            names[names.index(None)] = 'variable'\n",
    "            var_name = names\n",
    "        else:\n",
    "            missing_name_count = 0\n",
    "            for name in names:\n",
    "                if name is None:\n",
    "                    var_name.append('variable_{}'.format(missing_name_count))\n",
    "                    missing_name_count += 1\n",
    "                else:\n",
    "                    var_name.append(name)\n",
    "    if var_end is not None:\n",
    "        var_name = [vn + '_' + str(var_end) for vn in var_name]\n",
    "    \n",
    "    N = len(frame)\n",
    "    \n",
    "    non_id_ilocs = []\n",
    "    if value_vars != []:\n",
    "        for v in value_vars:\n",
    "            for i, v1 in enumerate(frame.columns):\n",
    "                if v == v1:\n",
    "                    non_id_ilocs.append(i)\n",
    "    else:\n",
    "        if id_vars == []:\n",
    "            non_id_ilocs = list(range(frame.shape[1]))\n",
    "        else:\n",
    "            for i, v in enumerate(frame.columns):\n",
    "                if v not in id_vars:\n",
    "                    non_id_ilocs.append(i)\n",
    "                        \n",
    "    K = len(non_id_ilocs)\n",
    "\n",
    "    mdata = {}\n",
    "    mcolumns = []\n",
    "    for col in id_vars:\n",
    "        pandas_obj = frame[col]\n",
    "        if isinstance(pandas_obj, DataFrame):\n",
    "            for i in range(pandas_obj.shape[1]):\n",
    "                col_name = col + '_id_' + str(i)\n",
    "                mdata[col_name] = np.tile(pandas_obj.iloc[:, i].values, K + extra_group)\n",
    "                mcolumns.append(col_name)\n",
    "        else:\n",
    "            mdata[col] = np.tile(pandas_obj, K + extra_group)\n",
    "            mcolumns.append(col)\n",
    "\n",
    "    values = np.concatenate([frame.iloc[:, i] for i in non_id_ilocs])\n",
    "    if extra_group > 0:\n",
    "        values = np.concatenate((values, np.full([N * extra_group], np.nan)))\n",
    "    mdata[value_name[0]] = values\n",
    "    \n",
    "    for i, col in enumerate(var_name):\n",
    "        values = frame.columns[non_id_ilocs]._get_level_values(i)\n",
    "        if stubnames:\n",
    "            regex = '^{0}{1}'.format(re.escape(value_name[0]), re.escape(sep))\n",
    "            values = to_numeric(values.str.replace(regex, ''), errors='ignore')\n",
    "        if isinstance(values, MultiIndex):\n",
    "            # asanyarray will keep the columns as an Index\n",
    "            values = np.asanyarray(values).repeat(N)\n",
    "        else: \n",
    "            data_list = []\n",
    "            for v in values.tolist():\n",
    "                data_list.extend([v] * N)\n",
    "            values = data_list\n",
    "        if extra_group > 0:\n",
    "            values = np.concatenate((values, np.full([N * extra_group], np.nan)))\n",
    "        mdata[col] = values\n",
    "    mcolumns += var_name + value_name\n",
    "    \n",
    "    return mdata, mcolumns\n",
    "\n",
    "\n",
    "@Appender(_shared_docs['melt'] %\n",
    "          dict(caller='pd.melt(df, ',\n",
    "               versionadded=\"\",\n",
    "               other='DataFrame.melt'))\n",
    "def melt(frame, id_vars=None, value_vars=None, var_name=None,\n",
    "         value_name='value', col_level=None, stubnames=False,\n",
    "         suffix=r'\\d+', sep=''):\n",
    "    def convert_to_list(val):\n",
    "        if val is None:\n",
    "            return []\n",
    "        elif not is_list_like(val):\n",
    "            return [val]\n",
    "        else:\n",
    "            return list(val)\n",
    "\n",
    "    def get_var_names(df, stub, sep, suffix):\n",
    "        regex = '^{0}{1}{2}$'.format(re.escape(stub), re.escape(sep), suffix)\n",
    "        col_return = [col for col in df.columns if re.match(regex, col)]\n",
    "        if col_return == []:\n",
    "            raise ValueError('No stubname {}'.format(stub))\n",
    "        return col_return\n",
    "\n",
    "    id_vars = convert_to_list(id_vars)\n",
    "    value_vars = convert_to_list(value_vars)\n",
    "    var_name = convert_to_list(var_name)\n",
    "    value_name = convert_to_list(value_name)\n",
    "    col_level = convert_to_list(col_level)\n",
    "\n",
    "    if stubnames:\n",
    "        if value_vars == []:\n",
    "            raise ValueError('Must provide stubnames as a list to value_vars')\n",
    "        value_name = value_vars\n",
    "        value_vars = [get_var_names(frame, stub, sep, suffix)\n",
    "                      for stub in value_vars]\n",
    "        if var_name == []:\n",
    "            var_name = ['variable_' + v for v in value_name]\n",
    "\n",
    "    if value_vars != [] and isinstance(value_vars[0], list):\n",
    "        if var_name != []:\n",
    "            if len(value_vars) != len(var_name):\n",
    "                raise ValueError('Number of inner lists of value_vars must '\n",
    "                                 'equal length of var_name '\n",
    "                                 '{} != {}'.format(len(value_vars),\n",
    "                                                   len(var_name)))\n",
    "        else:\n",
    "            var_name = [[]] * len(value_vars)\n",
    "\n",
    "        if len(value_name) > 1:\n",
    "            if len(value_vars) != len(value_name):\n",
    "                raise ValueError('Number of inner lists of value_vars must '\n",
    "                                 'equal length of value_name '\n",
    "                                 '{} != {}'.format(len(value_vars),\n",
    "                                                   len(value_name)))\n",
    "        elif not stubnames:\n",
    "            value_name = [value_name[0] + '_' + str(i) for i in range(len(value_vars))]\n",
    "\n",
    "        value_vars_length = []\n",
    "        for vv in value_vars:\n",
    "            count = 0\n",
    "            for col in frame.columns.values:\n",
    "                if col in vv:\n",
    "                    count += 1\n",
    "            value_vars_length.append(count)\n",
    "        max_group_len = max(value_vars_length)  \n",
    "\n",
    "        mdata_list = []\n",
    "        mcolumns_list = []\n",
    "        vars_zipped = zip(value_vars, var_name, value_name, value_vars_length)\n",
    "        for i, (val_v, var_n, val_n, vvl) in enumerate(vars_zipped):\n",
    "            var_n = convert_to_list(var_n)\n",
    "            val_n = convert_to_list(val_n)\n",
    "\n",
    "            id_vars_ = [] if i > 0 else id_vars\n",
    "            var_end = i if var_n == [] else None\n",
    "            \n",
    "            md, mc = _melt(frame, id_vars=id_vars_, value_vars=val_v,\n",
    "                       var_name=var_n, value_name=val_n,\n",
    "                       col_level=col_level, stubnames=stubnames,\n",
    "                       suffix=suffix, sep=sep, \n",
    "                       extra_group=max_group_len - vvl,\n",
    "                       var_end=var_end)\n",
    "\n",
    "            mdata_list.append(md)\n",
    "            mcolumns_list.append(mc)\n",
    "            \n",
    "        mdata = {}\n",
    "        for d in mdata_list:\n",
    "            mdata.update(d)\n",
    "            \n",
    "        mcolumns = [e for lst in mcolumns_list for e in lst]\n",
    "        return DataFrame(mdata, columns=mcolumns)\n",
    "\n",
    "    else:   \n",
    "        mdata, mcolumns =  _melt(frame, id_vars=id_vars, value_vars=value_vars,\n",
    "                             var_name=var_name, value_name=value_name,\n",
    "                             col_level=col_level, stubnames=stubnames,\n",
    "                             suffix=suffix, sep=sep)\n",
    "        return DataFrame(mdata, columns=mcolumns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Main enhancement\n",
    "Ability to simultaneously melt multiple groups of columns. Pass in a list of lists to `value_vars`. Importantly, groups do not have to be the same size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Name</th>\n",
       "      <th>Mango</th>\n",
       "      <th>Orange</th>\n",
       "      <th>Watermelon</th>\n",
       "      <th>Gin</th>\n",
       "      <th>Vodka</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Houston</td>\n",
       "      <td>Texas</td>\n",
       "      <td>Aria</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>40</td>\n",
       "      <td>16</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Texas</td>\n",
       "      <td>Penelope</td>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>99</td>\n",
       "      <td>200</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hoover</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Niko</td>\n",
       "      <td>90</td>\n",
       "      <td>14</td>\n",
       "      <td>43</td>\n",
       "      <td>34</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      City    State      Name  Mango  Orange  Watermelon  Gin  Vodka\n",
       "0  Houston    Texas      Aria      4      10          40   16     20\n",
       "1   Austin    Texas  Penelope     10       8          99  200     33\n",
       "2   Hoover  Alabama      Niko     90      14          43   34     18"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame({'City': ['Houston', 'Austin', 'Hoover'],\n",
    "                   'State': ['Texas', 'Texas', 'Alabama'],\n",
    "                   'Name':['Aria', 'Penelope', 'Niko'],\n",
    "                   'Mango':[4, 10, 90],\n",
    "                   'Orange': [10, 8, 14], \n",
    "                   'Watermelon':[40, 99, 43],\n",
    "                   'Gin':[16, 200, 34],\n",
    "                   'Vodka':[20, 33, 18]},\n",
    "                 columns=['City', 'State', 'Name', 'Mango', 'Orange', 'Watermelon', 'Gin', 'Vodka'])\n",
    "\n",
    "df_large = df.sample(100000, replace=True)\n",
    "df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Fruit</th>\n",
       "      <th>Pounds</th>\n",
       "      <th>Drink</th>\n",
       "      <th>Ounces</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Houston</td>\n",
       "      <td>Texas</td>\n",
       "      <td>Mango</td>\n",
       "      <td>4</td>\n",
       "      <td>Gin</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Texas</td>\n",
       "      <td>Mango</td>\n",
       "      <td>10</td>\n",
       "      <td>Gin</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hoover</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Mango</td>\n",
       "      <td>90</td>\n",
       "      <td>Gin</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Houston</td>\n",
       "      <td>Texas</td>\n",
       "      <td>Orange</td>\n",
       "      <td>10</td>\n",
       "      <td>Vodka</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Texas</td>\n",
       "      <td>Orange</td>\n",
       "      <td>8</td>\n",
       "      <td>Vodka</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Hoover</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Orange</td>\n",
       "      <td>14</td>\n",
       "      <td>Vodka</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Houston</td>\n",
       "      <td>Texas</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>40</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Texas</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>99</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Hoover</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>43</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      City    State       Fruit  Pounds  Drink  Ounces\n",
       "0  Houston    Texas       Mango       4    Gin    16.0\n",
       "1   Austin    Texas       Mango      10    Gin   200.0\n",
       "2   Hoover  Alabama       Mango      90    Gin    34.0\n",
       "3  Houston    Texas      Orange      10  Vodka    20.0\n",
       "4   Austin    Texas      Orange       8  Vodka    33.0\n",
       "5   Hoover  Alabama      Orange      14  Vodka    18.0\n",
       "6  Houston    Texas  Watermelon      40    nan     NaN\n",
       "7   Austin    Texas  Watermelon      99    nan     NaN\n",
       "8   Hoover  Alabama  Watermelon      43    nan     NaN"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "melt(df, id_vars=['City', 'State'], value_vars=[['Mango', 'Orange', 'Watermelon'], ['Gin', 'Vodka']], \n",
    "     var_name=['Fruit', 'Drink'], value_name=['Pounds', 'Ounces'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The current version of melt requires two separate melts and then a joining of the resulting frames. `pd.lreshape` cannot handle different sized groups."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'ValueError'> All column lists must be same length\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    pd.lreshape(df, {'temp':['yellow', 'green'], 'city':['FL']})\n",
    "except Exception as e:\n",
    "    print(type(e), e)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`lreshape` only works with equal-sized groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>City</th>\n",
       "      <th>Name</th>\n",
       "      <th>State</th>\n",
       "      <th>Watermelon</th>\n",
       "      <th>Fruit</th>\n",
       "      <th>Drink</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Houston</td>\n",
       "      <td>Aria</td>\n",
       "      <td>Texas</td>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Penelope</td>\n",
       "      <td>Texas</td>\n",
       "      <td>99</td>\n",
       "      <td>10</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hoover</td>\n",
       "      <td>Niko</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>43</td>\n",
       "      <td>90</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Houston</td>\n",
       "      <td>Aria</td>\n",
       "      <td>Texas</td>\n",
       "      <td>40</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Penelope</td>\n",
       "      <td>Texas</td>\n",
       "      <td>99</td>\n",
       "      <td>8</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Hoover</td>\n",
       "      <td>Niko</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>43</td>\n",
       "      <td>14</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      City      Name    State  Watermelon  Fruit  Drink\n",
       "0  Houston      Aria    Texas          40      4     16\n",
       "1   Austin  Penelope    Texas          99     10    200\n",
       "2   Hoover      Niko  Alabama          43     90     34\n",
       "3  Houston      Aria    Texas          40     10     20\n",
       "4   Austin  Penelope    Texas          99      8     33\n",
       "5   Hoover      Niko  Alabama          43     14     18"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.lreshape(df, {'Fruit':['Mango', 'Orange'], 'Drink':['Gin', 'Vodka']})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Slightly worse performance that `lreshape` but much better performance than the old `melt`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.3 ms ± 51.6 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit \n",
    "melt(df, id_vars=['City', 'State'], value_vars=[['Mango', 'Orange'], ['Gin', 'Vodka']], \n",
    "     var_name=['Fruit', 'Drink'], value_name=['Pounds', 'Ounces'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "984 µs ± 34.5 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit pd.lreshape(df, {'Fruit':['Mango', 'Orange'], 'Drink':['Gin', 'Vodka']})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Better performance against old melt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Fruit</th>\n",
       "      <th>Pounds</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Houston</td>\n",
       "      <td>Texas</td>\n",
       "      <td>Orange</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Texas</td>\n",
       "      <td>Orange</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hoover</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Orange</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Houston</td>\n",
       "      <td>Texas</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Texas</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Hoover</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Houston</td>\n",
       "      <td>Texas</td>\n",
       "      <td>Mango</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Texas</td>\n",
       "      <td>Mango</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Hoover</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Mango</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      City    State       Fruit  Pounds\n",
       "0  Houston    Texas      Orange      10\n",
       "1   Austin    Texas      Orange       8\n",
       "2   Hoover  Alabama      Orange      14\n",
       "3  Houston    Texas  Watermelon      40\n",
       "4   Austin    Texas  Watermelon      99\n",
       "5   Hoover  Alabama  Watermelon      43\n",
       "6  Houston    Texas       Mango       4\n",
       "7   Austin    Texas       Mango      10\n",
       "8   Hoover  Alabama       Mango      90"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "melt(df, id_vars=['City', 'State'], value_vars=['Orange', 'Watermelon', 'Mango'], \n",
    "     var_name='Fruit', value_name='Pounds')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "962 µs ± 22.1 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit \n",
    "melt(df, id_vars=['City', 'State'], value_vars=['Orange', 'Watermelon', 'Mango'], \n",
    "     var_name='Fruit', value_name='Pounds')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.79 ms ± 51 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit \n",
    "pd.melt(df, id_vars=['City', 'State'], value_vars=['Orange', 'Watermelon', 'Mango'], \n",
    "         var_name='Fruit', value_name='Pounds')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### wide_to_long functionality\n",
    "wide_to_long functionality was not exactly replicated. Instead of merging the suffixes into one columns they are kept separate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>group</th>\n",
       "      <th>exp_1</th>\n",
       "      <th>exp_2</th>\n",
       "      <th>res_1</th>\n",
       "      <th>res_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>a</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>b</td>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c</td>\n",
       "      <td>-9</td>\n",
       "      <td>14</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  group  exp_1  exp_2  res_1  res_3\n",
       "0     a      4     10      8     11\n",
       "1     b     10      8      5      0\n",
       "2     c     -9     14      4      7"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.DataFrame({'group': ['a', 'b', 'c'],\n",
    "                   'exp_1':[4, 10, -9],\n",
    "                   'exp_2': [10, 8, 14], \n",
    "                   'res_1':[8, 5, 4],\n",
    "                   'res_3':[11, 0, 7]}, columns=['group', 'exp_1', 'exp_2', 'res_1', 'res_3'])\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>group</th>\n",
       "      <th>variable_exp</th>\n",
       "      <th>exp</th>\n",
       "      <th>variable_res</th>\n",
       "      <th>res</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>a</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>b</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c</td>\n",
       "      <td>1</td>\n",
       "      <td>-9</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>a</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>b</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>c</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  group  variable_exp  exp  variable_res  res\n",
       "0     a             1    4             1    8\n",
       "1     b             1   10             1    5\n",
       "2     c             1   -9             1    4\n",
       "3     a             2   10             3   11\n",
       "4     b             2    8             3    0\n",
       "5     c             2   14             3    7"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "melt(df1, id_vars='group', value_vars=['exp','res'], stubnames=True, sep='_')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe thead tr:only-child th {\n",
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       "\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>exp</th>\n",
       "      <th>res</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group</th>\n",
       "      <th>num</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">a</th>\n",
       "      <th>1</th>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">b</th>\n",
       "      <th>1</th>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">c</th>\n",
       "      <th>1</th>\n",
       "      <td>-9.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            exp   res\n",
       "group num            \n",
       "a     1     4.0   8.0\n",
       "      2    10.0   NaN\n",
       "      3     NaN  11.0\n",
       "b     1    10.0   5.0\n",
       "      2     8.0   NaN\n",
       "      3     NaN   0.0\n",
       "c     1    -9.0   4.0\n",
       "      2    14.0   NaN\n",
       "      3     NaN   7.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.wide_to_long(df1, stubnames=['exp', 'res'], i='group', j='num', sep='_')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Performance is much better"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.66 ms ± 25.7 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit melt(df1, id_vars='group', value_vars=['exp','res'], stubnames=True, sep='_')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12.1 ms ± 203 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit pd.wide_to_long(df1, stubnames=['exp', 'res'], i='group', j='num', sep='_')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MultiIndex Support\n",
    "There was not much support in the original melt for MultiIndex DataFrames. This new melt allows for any number of column level selection."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">a</th>\n",
       "      <th colspan=\"2\" halign=\"left\">b</th>\n",
       "      <th colspan=\"3\" halign=\"left\">c</th>\n",
       "      <th>d</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">f</th>\n",
       "      <th colspan=\"2\" halign=\"left\">f</th>\n",
       "      <th colspan=\"3\" halign=\"left\">g</th>\n",
       "      <th>g</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>some vars</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Name</th>\n",
       "      <th>Mango</th>\n",
       "      <th>Orange</th>\n",
       "      <th>Watermelon</th>\n",
       "      <th>Gin</th>\n",
       "      <th>Vodka</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Houston</td>\n",
       "      <td>Texas</td>\n",
       "      <td>Aria</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>40</td>\n",
       "      <td>16</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Austin</td>\n",
       "      <td>Texas</td>\n",
       "      <td>Penelope</td>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>99</td>\n",
       "      <td>200</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hoover</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Niko</td>\n",
       "      <td>90</td>\n",
       "      <td>14</td>\n",
       "      <td>43</td>\n",
       "      <td>34</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 a                  b            c                     d\n",
       "                 f                  f            g                     g\n",
       "some vars     City    State      Name Mango Orange Watermelon  Gin Vodka\n",
       "0          Houston    Texas      Aria     4     10         40   16    20\n",
       "1           Austin    Texas  Penelope    10      8         99  200    33\n",
       "2           Hoover  Alabama      Niko    90     14         43   34    18"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = df.copy()\n",
    "df2.columns = pd.MultiIndex.from_arrays([list('aabbcccd'), list('ffffgggg'), df.columns], \n",
    "                                       names=[None, None, 'some vars'])\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>(a, f, State)</th>\n",
       "      <th>variable_0</th>\n",
       "      <th>variable_1</th>\n",
       "      <th>some vars</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Texas</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Name</td>\n",
       "      <td>Aria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Texas</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Name</td>\n",
       "      <td>Penelope</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Name</td>\n",
       "      <td>Niko</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Texas</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Texas</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  (a, f, State) variable_0 variable_1   some vars     value\n",
       "0         Texas          b          f        Name      Aria\n",
       "1         Texas          b          f        Name  Penelope\n",
       "2       Alabama          b          f        Name      Niko\n",
       "3         Texas          c          g  Watermelon        40\n",
       "4         Texas          c          g  Watermelon        99\n",
       "5       Alabama          c          g  Watermelon        43"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "melt(df2, id_vars=[('a', 'f', 'State')], value_vars=[('b', 'f', 'Name'), ('c', 'g', 'Watermelon')])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Slight break in the API, uses column level if available."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>(a, f, State)</th>\n",
       "      <th>variable_0</th>\n",
       "      <th>variable_1</th>\n",
       "      <th>variable_2</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Texas</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Name</td>\n",
       "      <td>Aria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Texas</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Name</td>\n",
       "      <td>Penelope</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Name</td>\n",
       "      <td>Niko</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Texas</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Texas</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  (a, f, State) variable_0 variable_1  variable_2     value\n",
       "0         Texas          b          f        Name      Aria\n",
       "1         Texas          b          f        Name  Penelope\n",
       "2       Alabama          b          f        Name      Niko\n",
       "3         Texas          c          g  Watermelon        40\n",
       "4         Texas          c          g  Watermelon        99\n",
       "5       Alabama          c          g  Watermelon        43"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.melt(df2, id_vars=[('a', 'f', 'State')], value_vars=[('b', 'f', 'Name'), ('c', 'g', 'Watermelon')])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>(a, f, State)</th>\n",
       "      <th>variable_0_0</th>\n",
       "      <th>variable_1_0</th>\n",
       "      <th>some vars_0</th>\n",
       "      <th>value_0</th>\n",
       "      <th>variable_0_1</th>\n",
       "      <th>variable_1_1</th>\n",
       "      <th>some vars_1</th>\n",
       "      <th>value_1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Texas</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Name</td>\n",
       "      <td>Aria</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Mango</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Texas</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Name</td>\n",
       "      <td>Penelope</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Mango</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Name</td>\n",
       "      <td>Niko</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Mango</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Texas</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>40</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Orange</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Texas</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>99</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Orange</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>43</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Orange</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Texas</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>d</td>\n",
       "      <td>g</td>\n",
       "      <td>Vodka</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Texas</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>d</td>\n",
       "      <td>g</td>\n",
       "      <td>Vodka</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>d</td>\n",
       "      <td>g</td>\n",
       "      <td>Vodka</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  (a, f, State) variable_0_0 variable_1_0 some vars_0   value_0 variable_0_1  \\\n",
       "0         Texas            b            f        Name      Aria            b   \n",
       "1         Texas            b            f        Name  Penelope            b   \n",
       "2       Alabama            b            f        Name      Niko            b   \n",
       "3         Texas            c            g  Watermelon        40            c   \n",
       "4         Texas            c            g  Watermelon        99            c   \n",
       "5       Alabama            c            g  Watermelon        43            c   \n",
       "6         Texas          nan          nan         nan       NaN            d   \n",
       "7         Texas          nan          nan         nan       NaN            d   \n",
       "8       Alabama          nan          nan         nan       NaN            d   \n",
       "\n",
       "  variable_1_1 some vars_1  value_1  \n",
       "0            f       Mango        4  \n",
       "1            f       Mango       10  \n",
       "2            f       Mango       90  \n",
       "3            g      Orange       10  \n",
       "4            g      Orange        8  \n",
       "5            g      Orange       14  \n",
       "6            g       Vodka       20  \n",
       "7            g       Vodka       33  \n",
       "8            g       Vodka       18  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "melt(df2, id_vars=[('a', 'f', 'State')], value_vars=[[('b', 'f', 'Name'), ('c', 'g', 'Watermelon')],\n",
    "                                                   [('b','f','Mango'), ('c','g', 'Orange'), ('d', 'g', 'Vodka')]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Renaming multiple levels with multiple groups requires var_name to be a list of lists where the number of inner lists matches the number of groups and the lengths of the inner lists match the number of column levels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>(a, f, State)</th>\n",
       "      <th>myvar1</th>\n",
       "      <th>myvar2</th>\n",
       "      <th>myvar3</th>\n",
       "      <th>some values</th>\n",
       "      <th>next_myvar1</th>\n",
       "      <th>next_myvar2</th>\n",
       "      <th>next_myvar3</th>\n",
       "      <th>more_values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Texas</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Name</td>\n",
       "      <td>Aria</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Mango</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Texas</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Name</td>\n",
       "      <td>Penelope</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Mango</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Name</td>\n",
       "      <td>Niko</td>\n",
       "      <td>b</td>\n",
       "      <td>f</td>\n",
       "      <td>Mango</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Texas</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>40</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Orange</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Texas</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>99</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Orange</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Watermelon</td>\n",
       "      <td>43</td>\n",
       "      <td>c</td>\n",
       "      <td>g</td>\n",
       "      <td>Orange</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Texas</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>d</td>\n",
       "      <td>g</td>\n",
       "      <td>Vodka</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Texas</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>d</td>\n",
       "      <td>g</td>\n",
       "      <td>Vodka</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>d</td>\n",
       "      <td>g</td>\n",
       "      <td>Vodka</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  (a, f, State) myvar1 myvar2      myvar3 some values next_myvar1 next_myvar2  \\\n",
       "0         Texas      b      f        Name        Aria           b           f   \n",
       "1         Texas      b      f        Name    Penelope           b           f   \n",
       "2       Alabama      b      f        Name        Niko           b           f   \n",
       "3         Texas      c      g  Watermelon          40           c           g   \n",
       "4         Texas      c      g  Watermelon          99           c           g   \n",
       "5       Alabama      c      g  Watermelon          43           c           g   \n",
       "6         Texas    nan    nan         nan         NaN           d           g   \n",
       "7         Texas    nan    nan         nan         NaN           d           g   \n",
       "8       Alabama    nan    nan         nan         NaN           d           g   \n",
       "\n",
       "  next_myvar3  more_values  \n",
       "0       Mango            4  \n",
       "1       Mango           10  \n",
       "2       Mango           90  \n",
       "3      Orange           10  \n",
       "4      Orange            8  \n",
       "5      Orange           14  \n",
       "6       Vodka           20  \n",
       "7       Vodka           33  \n",
       "8       Vodka           18  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "melt(df2, id_vars=[('a', 'f', 'State')], value_vars=[[('b', 'f', 'Name'), ('c', 'g', 'Watermelon')],\n",
    "                                                   [('b','f','Mango'), ('c','g', 'Orange'), ('d', 'g', 'Vodka')]],\n",
    "    var_name=[['myvar1', 'myvar2', 'myvar3'],['next_myvar1', 'next_myvar2', 'next_myvar3']],\n",
    "    value_name=['some values', 'more_values'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Choose any subset of column levels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>(a, City)</th>\n",
       "      <th>variable</th>\n",
       "      <th>some vars</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Houston</td>\n",
       "      <td>a</td>\n",
       "      <td>State</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Austin</td>\n",
       "      <td>a</td>\n",
       "      <td>State</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hoover</td>\n",
       "      <td>a</td>\n",
       "      <td>State</td>\n",
       "      <td>Alabama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Houston</td>\n",
       "      <td>b</td>\n",
       "      <td>Name</td>\n",
       "      <td>Aria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Austin</td>\n",
       "      <td>b</td>\n",
       "      <td>Name</td>\n",
       "      <td>Penelope</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Hoover</td>\n",
       "      <td>b</td>\n",
       "      <td>Name</td>\n",
       "      <td>Niko</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Houston</td>\n",
       "      <td>b</td>\n",
       "      <td>Mango</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Austin</td>\n",
       "      <td>b</td>\n",
       "      <td>Mango</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Hoover</td>\n",
       "      <td>b</td>\n",
       "      <td>Mango</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Houston</td>\n",
       "      <td>c</td>\n",
       "      <td>Orange</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  (a, City) variable some vars     value\n",
       "0   Houston        a     State     Texas\n",
       "1    Austin        a     State     Texas\n",
       "2    Hoover        a     State   Alabama\n",
       "3   Houston        b      Name      Aria\n",
       "4    Austin        b      Name  Penelope\n",
       "5    Hoover        b      Name      Niko\n",
       "6   Houston        b     Mango         4\n",
       "7    Austin        b     Mango        10\n",
       "8    Hoover        b     Mango        90\n",
       "9   Houston        c    Orange        10"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "melt(df2, id_vars=[('a', 'City')], col_level=[0, 'some vars']).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mango</th>\n",
       "      <th>Watermelon</th>\n",
       "      <th>Orange</th>\n",
       "      <th>some vars</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>40</td>\n",
       "      <td>10</td>\n",
       "      <td>City</td>\n",
       "      <td>Houston</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>99</td>\n",
       "      <td>8</td>\n",
       "      <td>City</td>\n",
       "      <td>Austin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>90</td>\n",
       "      <td>43</td>\n",
       "      <td>14</td>\n",
       "      <td>City</td>\n",
       "      <td>Hoover</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>40</td>\n",
       "      <td>10</td>\n",
       "      <td>State</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10</td>\n",
       "      <td>99</td>\n",
       "      <td>8</td>\n",
       "      <td>State</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Mango  Watermelon  Orange some vars    value\n",
       "0      4          40      10      City  Houston\n",
       "1     10          99       8      City   Austin\n",
       "2     90          43      14      City   Hoover\n",
       "3      4          40      10     State    Texas\n",
       "4     10          99       8     State    Texas"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "melt(df2, id_vars=['Mango', 'Watermelon', 'Orange'], col_level=2).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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