Python-Data-Visualization.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# seaborn **"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set(style=\"ticks\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = sns.load_dataset(\"tips\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip     sex smoker  day    time  size\n",
       "0       16.99  1.01  Female     No  Sun  Dinner     2\n",
       "1       10.34  1.66    Male     No  Sun  Dinner     3\n",
       "2       21.01  3.50    Male     No  Sun  Dinner     3\n",
       "3       23.68  3.31    Male     No  Sun  Dinner     2\n",
       "4       24.59  3.61  Female     No  Sun  Dinner     4"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a23cec860>"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# to check missing values\n",
    "sns.heatmap(df.isnull(),yticklabels=False,cbar=False,cmap='viridis')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Distribution Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/mk194903/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a19f14518>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize distribution\n",
    "sns.distplot(df['total_bill']) #histogram, kde(kernel density estimation) is line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1b7286a0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Shows density similar to distplot(histogram)\n",
    "sns.rugplot(df['total_bill'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/mk194903/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n",
      "/Users/mk194903/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x1a1a0050b8>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# combine 2 distribution plots\n",
    "sns.jointplot(x='total_bill', y='tip', data=df, kind='reg') #kind -\"scatter\",\"reg\"(regression),\"resid\", \"kde\",\"hex\"(darker if more points in hex)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1a1a87ae10>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 609.375x540 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# pair plot - do joint plot on every possible combination(numerical columns), Hue is to distinguish dots as per category\n",
    "sns.pairplot(data=df, hue='sex')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Categorical Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1baa6b38>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='sex', y='total_bill', data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1bb090b8>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='sex', data=df) shows count for category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1bebd9e8>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visually displaying the data distribution through their quartiles. \n",
    "sns.boxplot(x='day', y='total_bill', data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1bd67e80>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='day', y='total_bill', data=df, hue='smoker') #spliting as per smoker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1bfb3e48>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.stripplot(x=\"day\", y=\"total_bill\", data=df,jitter=True,hue='sex',palette='Set1')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MatrixPlot\n",
    "Column and row index both should be label"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Heat map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>total_bill</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.675734</td>\n",
       "      <td>0.598315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tip</th>\n",
       "      <td>0.675734</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.489299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>size</th>\n",
       "      <td>0.598315</td>\n",
       "      <td>0.489299</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            total_bill       tip      size\n",
       "total_bill    1.000000  0.675734  0.598315\n",
       "tip           0.675734  1.000000  0.489299\n",
       "size          0.598315  0.489299  1.000000"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#To show heatmap data should be in matrix form.\n",
    "tc = df.corr()   #shows corelation in matrix form\n",
    "tc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1c393160>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(tc, annot=True, cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "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>year</th>\n",
       "      <th>month</th>\n",
       "      <th>passengers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1949</td>\n",
       "      <td>January</td>\n",
       "      <td>112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1949</td>\n",
       "      <td>February</td>\n",
       "      <td>118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1949</td>\n",
       "      <td>March</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1949</td>\n",
       "      <td>April</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1949</td>\n",
       "      <td>May</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year     month  passengers\n",
       "0  1949   January         112\n",
       "1  1949  February         118\n",
       "2  1949     March         132\n",
       "3  1949     April         129\n",
       "4  1949       May         121"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flights = sns.load_dataset('flights')\n",
    "flights.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "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>year</th>\n",
       "      <th>1949</th>\n",
       "      <th>1950</th>\n",
       "      <th>1951</th>\n",
       "      <th>1952</th>\n",
       "      <th>1953</th>\n",
       "      <th>1954</th>\n",
       "      <th>1955</th>\n",
       "      <th>1956</th>\n",
       "      <th>1957</th>\n",
       "      <th>1958</th>\n",
       "      <th>1959</th>\n",
       "      <th>1960</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>January</th>\n",
       "      <td>112</td>\n",
       "      <td>115</td>\n",
       "      <td>145</td>\n",
       "      <td>171</td>\n",
       "      <td>196</td>\n",
       "      <td>204</td>\n",
       "      <td>242</td>\n",
       "      <td>284</td>\n",
       "      <td>315</td>\n",
       "      <td>340</td>\n",
       "      <td>360</td>\n",
       "      <td>417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>February</th>\n",
       "      <td>118</td>\n",
       "      <td>126</td>\n",
       "      <td>150</td>\n",
       "      <td>180</td>\n",
       "      <td>196</td>\n",
       "      <td>188</td>\n",
       "      <td>233</td>\n",
       "      <td>277</td>\n",
       "      <td>301</td>\n",
       "      <td>318</td>\n",
       "      <td>342</td>\n",
       "      <td>391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>March</th>\n",
       "      <td>132</td>\n",
       "      <td>141</td>\n",
       "      <td>178</td>\n",
       "      <td>193</td>\n",
       "      <td>236</td>\n",
       "      <td>235</td>\n",
       "      <td>267</td>\n",
       "      <td>317</td>\n",
       "      <td>356</td>\n",
       "      <td>362</td>\n",
       "      <td>406</td>\n",
       "      <td>419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>April</th>\n",
       "      <td>129</td>\n",
       "      <td>135</td>\n",
       "      <td>163</td>\n",
       "      <td>181</td>\n",
       "      <td>235</td>\n",
       "      <td>227</td>\n",
       "      <td>269</td>\n",
       "      <td>313</td>\n",
       "      <td>348</td>\n",
       "      <td>348</td>\n",
       "      <td>396</td>\n",
       "      <td>461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>May</th>\n",
       "      <td>121</td>\n",
       "      <td>125</td>\n",
       "      <td>172</td>\n",
       "      <td>183</td>\n",
       "      <td>229</td>\n",
       "      <td>234</td>\n",
       "      <td>270</td>\n",
       "      <td>318</td>\n",
       "      <td>355</td>\n",
       "      <td>363</td>\n",
       "      <td>420</td>\n",
       "      <td>472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>June</th>\n",
       "      <td>135</td>\n",
       "      <td>149</td>\n",
       "      <td>178</td>\n",
       "      <td>218</td>\n",
       "      <td>243</td>\n",
       "      <td>264</td>\n",
       "      <td>315</td>\n",
       "      <td>374</td>\n",
       "      <td>422</td>\n",
       "      <td>435</td>\n",
       "      <td>472</td>\n",
       "      <td>535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>July</th>\n",
       "      <td>148</td>\n",
       "      <td>170</td>\n",
       "      <td>199</td>\n",
       "      <td>230</td>\n",
       "      <td>264</td>\n",
       "      <td>302</td>\n",
       "      <td>364</td>\n",
       "      <td>413</td>\n",
       "      <td>465</td>\n",
       "      <td>491</td>\n",
       "      <td>548</td>\n",
       "      <td>622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>August</th>\n",
       "      <td>148</td>\n",
       "      <td>170</td>\n",
       "      <td>199</td>\n",
       "      <td>242</td>\n",
       "      <td>272</td>\n",
       "      <td>293</td>\n",
       "      <td>347</td>\n",
       "      <td>405</td>\n",
       "      <td>467</td>\n",
       "      <td>505</td>\n",
       "      <td>559</td>\n",
       "      <td>606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>September</th>\n",
       "      <td>136</td>\n",
       "      <td>158</td>\n",
       "      <td>184</td>\n",
       "      <td>209</td>\n",
       "      <td>237</td>\n",
       "      <td>259</td>\n",
       "      <td>312</td>\n",
       "      <td>355</td>\n",
       "      <td>404</td>\n",
       "      <td>404</td>\n",
       "      <td>463</td>\n",
       "      <td>508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>October</th>\n",
       "      <td>119</td>\n",
       "      <td>133</td>\n",
       "      <td>162</td>\n",
       "      <td>191</td>\n",
       "      <td>211</td>\n",
       "      <td>229</td>\n",
       "      <td>274</td>\n",
       "      <td>306</td>\n",
       "      <td>347</td>\n",
       "      <td>359</td>\n",
       "      <td>407</td>\n",
       "      <td>461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>November</th>\n",
       "      <td>104</td>\n",
       "      <td>114</td>\n",
       "      <td>146</td>\n",
       "      <td>172</td>\n",
       "      <td>180</td>\n",
       "      <td>203</td>\n",
       "      <td>237</td>\n",
       "      <td>271</td>\n",
       "      <td>305</td>\n",
       "      <td>310</td>\n",
       "      <td>362</td>\n",
       "      <td>390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>December</th>\n",
       "      <td>118</td>\n",
       "      <td>140</td>\n",
       "      <td>166</td>\n",
       "      <td>194</td>\n",
       "      <td>201</td>\n",
       "      <td>229</td>\n",
       "      <td>278</td>\n",
       "      <td>306</td>\n",
       "      <td>336</td>\n",
       "      <td>337</td>\n",
       "      <td>405</td>\n",
       "      <td>432</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "year       1949  1950  1951  1952  1953  1954  1955  1956  1957  1958  1959  \\\n",
       "month                                                                         \n",
       "January     112   115   145   171   196   204   242   284   315   340   360   \n",
       "February    118   126   150   180   196   188   233   277   301   318   342   \n",
       "March       132   141   178   193   236   235   267   317   356   362   406   \n",
       "April       129   135   163   181   235   227   269   313   348   348   396   \n",
       "May         121   125   172   183   229   234   270   318   355   363   420   \n",
       "June        135   149   178   218   243   264   315   374   422   435   472   \n",
       "July        148   170   199   230   264   302   364   413   465   491   548   \n",
       "August      148   170   199   242   272   293   347   405   467   505   559   \n",
       "September   136   158   184   209   237   259   312   355   404   404   463   \n",
       "October     119   133   162   191   211   229   274   306   347   359   407   \n",
       "November    104   114   146   172   180   203   237   271   305   310   362   \n",
       "December    118   140   166   194   201   229   278   306   336   337   405   \n",
       "\n",
       "year       1960  \n",
       "month            \n",
       "January     417  \n",
       "February    391  \n",
       "March       419  \n",
       "April       461  \n",
       "May         472  \n",
       "June        535  \n",
       "July        622  \n",
       "August      606  \n",
       "September   508  \n",
       "October     461  \n",
       "November    390  \n",
       "December    432  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flights.pivot_table(values='passengers',index='month',columns='year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1c59e7b8>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pvflights = flights.pivot_table(values='passengers',index='month',columns='year')\n",
    "sns.heatmap(pvflights)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### clustermap\n",
    "\n",
    "The clustermap uses **hierarchal clustering** to produce a clustered version of the heatmap. For example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.matrix.ClusterGrid at 0x1a2162e198>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.clustermap(pvflights,cmap='coolwarm',standard_scale=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1a2221b240>"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 429.375x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(x='total_bill',y='tip',data=df,hue='sex')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas Built-in Data Visualization **"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a2253f5c0>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['total_bill'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a23774dd8>"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1c376ba8>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.scatter(x='total_bill',y='tip',c='size',cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Thank You"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
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