learn_pandas_20200903_处理日期函数.ipynb

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  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "%matplotlib inline\n",
    "\n",
    "fpath = './shanghai_weather/shanghai_weather_2019.csv'\n",
    "df = pd.read_csv(fpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.loc[:, 'bWendu'] = df['bWendu'].str.replace(\"℃\", \"\").astype('int32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.loc[:, 'yWendu'] = df['yWendu'].str.replace(\"℃\", \"\").astype('int32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "          ymd  bWendu  yWendu tianqi fengxiang fengli  aqi aqiInfo  aqiLevel\n0  2019-01-01       6       3   阴~多云       西北风     3级   39       优         1\n1  2019-01-02       8       4   阴~多云       东北风     2级   86       良         2\n2  2019-01-03      10       8  多云~小雨       东北风     2级   71       良         2\n3  2019-01-04      10       8     小雨       东南风     2级   33       优         1\n4  2019-01-05      10       5     小雨       西北风     2级   46       优         1",
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     },
     "metadata": {},
     "execution_count": 5
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.set_index(pd.to_datetime(df['ymd']), inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "                   ymd  bWendu  yWendu tianqi fengxiang fengli  aqi aqiInfo  \\\nymd                                                                           \n2019-01-01  2019-01-01       6       3   阴~多云       西北风     3级   39       优   \n2019-01-02  2019-01-02       8       4   阴~多云       东北风     2级   86       良   \n2019-01-03  2019-01-03      10       8  多云~小雨       东北风     2级   71       良   \n2019-01-04  2019-01-04      10       8     小雨       东南风     2级   33       优   \n2019-01-05  2019-01-05      10       5     小雨       西北风     2级   46       优   \n\n            aqiLevel  \nymd                   \n2019-01-01         1  \n2019-01-02         2  \n2019-01-03         2  \n2019-01-04         1  \n2019-01-05         1  ",
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     },
     "metadata": {},
     "execution_count": 7
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "Timestamp('2019-01-01 00:00:00')"
     },
     "metadata": {},
     "execution_count": 9
    }
   ],
   "source": [
    "df.index[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "Int64Index([ 1,  1,  1,  1,  1,  1,  2,  2,  2,  2,\n            ...\n            51, 52, 52, 52, 52, 52, 52, 52,  1,  1],\n           dtype='int64', name='ymd', length=365)"
     },
     "metadata": {},
     "execution_count": 10
    }
   ],
   "source": [
    "df.index.week"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "Int64Index([ 1,  1,  1,  1,  1,  1,  1,  1,  1,  1,\n            ...\n            12, 12, 12, 12, 12, 12, 12, 12, 12, 12],\n           dtype='int64', name='ymd', length=365)"
     },
     "metadata": {},
     "execution_count": 11
    }
   ],
   "source": [
    "df.index.month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "Int64Index([1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n            ...\n            4, 4, 4, 4, 4, 4, 4, 4, 4, 4],\n           dtype='int64', name='ymd', length=365)"
     },
     "metadata": {},
     "execution_count": 12
    }
   ],
   "source": [
    "df.index.quarter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "df_week = df.groupby(df.index.week)['bWendu'].agg([np.max, np.min, np.mean])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "<AxesSubplot:xlabel='ymd'>"
     },
     "metadata": {},
     "execution_count": 19
    },
    {
     "output_type": "display_data",
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "df_week.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ]
}