{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Seaborn-柱状图和热力图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plp\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 使用 Seaborn 生成测试数据\n",
    "df1 = sns.load_dataset('flights')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df1.pivot(index='month', columns='year', values='passengers')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a21974358>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 热力图\n",
    "sns.heatmap(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a21cba400>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a221f11d0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 柱状图\n",
    "s = df.sum()\n",
    "sns.barplot(x=s.index, y=s.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a22280e48>"
      ]
     },
     "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": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "s.plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}