{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#数据读入\n",
"data_lm = pd.read_table('0430.txt',encoding='GBK')\n",
"data_tm = pd.read_table('0520.txt',encoding='GBK')\n",
"kuandai = pd.concat([data_lm,data_tm])"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#创建中间表\n",
"kd_tm = kuandai.loc[kuandai['入网时间']//100 == 201805]#本月数据\n",
"kd_lm = kuandai.loc[(kuandai['入网时间']//100 == 201804)&(kuandai['入网时间'] % 100 <= 20)]#上月数据\n",
"ec_tm = kd_tm.loc[kd_tm['十六大渠道'] == '电子渠道']#本月电子渠道数据\n",
"ec_lm = kd_lm.loc[kd_lm['十六大渠道'] == '电子渠道']#上月电子渠道数据"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true,
"scrolled": false
},
"outputs": [],
"source": [
"#计算当月宽带业务发展量\n",
"rst = ec_tm.groupby('分公司')['统计值'].sum()\n",
"rst.name = '发展量'"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"分公司\n",
"东莞 0.889671\n",
"中山 1.392544\n",
"云浮 0.250000\n",
"佛山 1.091286\n",
"广州 1.034507\n",
"惠州 1.142857\n",
"揭阳 NaN\n",
"梅州 1.038462\n",
"汕头 0.588235\n",
"汕尾 0.583333\n",
"江门 0.578313\n",
"河源 0.400000\n",
"深圳 0.967887\n",
"清远 1.684211\n",
"湛江 1.444444\n",
"潮州 0.175676\n",
"珠海 0.882937\n",
"肇庆 1.260870\n",
"茂名 0.888889\n",
"阳江 0.800000\n",
"韶关 0.725962\n",
"Name: 环比, dtype: float64"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#计算发展量环比\n",
"rst_huanbi = rst / ec_lm.groupby('分公司')['统计值'].sum()\n",
"rst_huanbi.name = \"环比\"\n",
"rst_huanbi"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"分公司\n",
"东莞 0.268549\n",
"中山 0.091144\n",
"云浮 0.000397\n",
"佛山 0.012738\n",
"广州 0.030841\n",
"惠州 0.075696\n",
"揭阳 0.000659\n",
"梅州 0.004713\n",
"汕头 0.001327\n",
"汕尾 0.002309\n",
"江门 0.006345\n",
"河源 0.000546\n",
"深圳 0.085430\n",
"清远 0.004692\n",
"湛江 0.002500\n",
"潮州 0.006424\n",
"珠海 0.073724\n",
"肇庆 0.005881\n",
"茂名 0.001870\n",
"阳江 0.000576\n",
"韶关 0.024946\n",
"Name: 渠道占比, dtype: float64"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#计算渠道占比\n",
"rst_zhanbi = rst / kd_tm.groupby('分公司')['统计值'].sum()\n",
"rst_zhanbi.name = \"渠道占比\"\n",
"rst_zhanbi"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" 发展量 | \n",
" 环比 | \n",
" 渠道占比 | \n",
"
\n",
" \n",
" 分公司 | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" \n",
" \n",
" 东莞 | \n",
" 6193.0 | \n",
" 0.889671 | \n",
" 0.268549 | \n",
"
\n",
" \n",
" 中山 | \n",
" 1270.0 | \n",
" 1.392544 | \n",
" 0.091144 | \n",
"
\n",
" \n",
" 云浮 | \n",
" 1.0 | \n",
" 0.250000 | \n",
" 0.000397 | \n",
"
\n",
" \n",
" 佛山 | \n",
" 263.0 | \n",
" 1.091286 | \n",
" 0.012738 | \n",
"
\n",
" \n",
" 广州 | \n",
" 1469.0 | \n",
" 1.034507 | \n",
" 0.030841 | \n",
"
\n",
" \n",
" 惠州 | \n",
" 840.0 | \n",
" 1.142857 | \n",
" 0.075696 | \n",
"
\n",
" \n",
" 揭阳 | \n",
" 4.0 | \n",
" NaN | \n",
" 0.000659 | \n",
"
\n",
" \n",
" 梅州 | \n",
" 27.0 | \n",
" 1.038462 | \n",
" 0.004713 | \n",
"
\n",
" \n",
" 汕头 | \n",
" 10.0 | \n",
" 0.588235 | \n",
" 0.001327 | \n",
"
\n",
" \n",
" 汕尾 | \n",
" 7.0 | \n",
" 0.583333 | \n",
" 0.002309 | \n",
"
\n",
" \n",
" 江门 | \n",
" 48.0 | \n",
" 0.578313 | \n",
" 0.006345 | \n",
"
\n",
" \n",
" 河源 | \n",
" 2.0 | \n",
" 0.400000 | \n",
" 0.000546 | \n",
"
\n",
" \n",
" 深圳 | \n",
" 3647.0 | \n",
" 0.967887 | \n",
" 0.085430 | \n",
"
\n",
" \n",
" 清远 | \n",
" 32.0 | \n",
" 1.684211 | \n",
" 0.004692 | \n",
"
\n",
" \n",
" 湛江 | \n",
" 13.0 | \n",
" 1.444444 | \n",
" 0.002500 | \n",
"
\n",
" \n",
" 潮州 | \n",
" 39.0 | \n",
" 0.175676 | \n",
" 0.006424 | \n",
"
\n",
" \n",
" 珠海 | \n",
" 445.0 | \n",
" 0.882937 | \n",
" 0.073724 | \n",
"
\n",
" \n",
" 肇庆 | \n",
" 29.0 | \n",
" 1.260870 | \n",
" 0.005881 | \n",
"
\n",
" \n",
" 茂名 | \n",
" 8.0 | \n",
" 0.888889 | \n",
" 0.001870 | \n",
"
\n",
" \n",
" 阳江 | \n",
" 4.0 | \n",
" 0.800000 | \n",
" 0.000576 | \n",
"
\n",
" \n",
" 韶关 | \n",
" 151.0 | \n",
" 0.725962 | \n",
" 0.024946 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" 发展量 环比 渠道占比\n",
"分公司 \n",
"东莞 6193.0 0.889671 0.268549\n",
"中山 1270.0 1.392544 0.091144\n",
"云浮 1.0 0.250000 0.000397\n",
"佛山 263.0 1.091286 0.012738\n",
"广州 1469.0 1.034507 0.030841\n",
"惠州 840.0 1.142857 0.075696\n",
"揭阳 4.0 NaN 0.000659\n",
"梅州 27.0 1.038462 0.004713\n",
"汕头 10.0 0.588235 0.001327\n",
"汕尾 7.0 0.583333 0.002309\n",
"江门 48.0 0.578313 0.006345\n",
"河源 2.0 0.400000 0.000546\n",
"深圳 3647.0 0.967887 0.085430\n",
"清远 32.0 1.684211 0.004692\n",
"湛江 13.0 1.444444 0.002500\n",
"潮州 39.0 0.175676 0.006424\n",
"珠海 445.0 0.882937 0.073724\n",
"肇庆 29.0 1.260870 0.005881\n",
"茂名 8.0 0.888889 0.001870\n",
"阳江 4.0 0.800000 0.000576\n",
"韶关 151.0 0.725962 0.024946"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#合并各字段\n",
"result = pd.concat([rst,rst_huanbi,rst_zhanbi],axis=1)\n",
"result"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" 发展量 | \n",
" 环比 | \n",
" 渠道占比 | \n",
"
\n",
" \n",
" 分公司 | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" \n",
" \n",
" 深圳 | \n",
" 3647.0 | \n",
" 0.967887 | \n",
" 0.085430 | \n",
"
\n",
" \n",
" 广州 | \n",
" 1469.0 | \n",
" 1.034507 | \n",
" 0.030841 | \n",
"
\n",
" \n",
" 佛山 | \n",
" 263.0 | \n",
" 1.091286 | \n",
" 0.012738 | \n",
"
\n",
" \n",
" 东莞 | \n",
" 6193.0 | \n",
" 0.889671 | \n",
" 0.268549 | \n",
"
\n",
" \n",
" 中山 | \n",
" 1270.0 | \n",
" 1.392544 | \n",
" 0.091144 | \n",
"
\n",
" \n",
" 惠州 | \n",
" 840.0 | \n",
" 1.142857 | \n",
" 0.075696 | \n",
"
\n",
" \n",
" 江门 | \n",
" 48.0 | \n",
" 0.578313 | \n",
" 0.006345 | \n",
"
\n",
" \n",
" 珠海 | \n",
" 445.0 | \n",
" 0.882937 | \n",
" 0.073724 | \n",
"
\n",
" \n",
" 汕头 | \n",
" 10.0 | \n",
" 0.588235 | \n",
" 0.001327 | \n",
"
\n",
" \n",
" 揭阳 | \n",
" 4.0 | \n",
" 0.000000 | \n",
" 0.000659 | \n",
"
\n",
" \n",
" 潮州 | \n",
" 39.0 | \n",
" 0.175676 | \n",
" 0.006424 | \n",
"
\n",
" \n",
" 汕尾 | \n",
" 7.0 | \n",
" 0.583333 | \n",
" 0.002309 | \n",
"
\n",
" \n",
" 湛江 | \n",
" 13.0 | \n",
" 1.444444 | \n",
" 0.002500 | \n",
"
\n",
" \n",
" 茂名 | \n",
" 8.0 | \n",
" 0.888889 | \n",
" 0.001870 | \n",
"
\n",
" \n",
" 阳江 | \n",
" 4.0 | \n",
" 0.800000 | \n",
" 0.000576 | \n",
"
\n",
" \n",
" 云浮 | \n",
" 1.0 | \n",
" 0.250000 | \n",
" 0.000397 | \n",
"
\n",
" \n",
" 肇庆 | \n",
" 29.0 | \n",
" 1.260870 | \n",
" 0.005881 | \n",
"
\n",
" \n",
" 梅州 | \n",
" 27.0 | \n",
" 1.038462 | \n",
" 0.004713 | \n",
"
\n",
" \n",
" 清远 | \n",
" 32.0 | \n",
" 1.684211 | \n",
" 0.004692 | \n",
"
\n",
" \n",
" 河源 | \n",
" 2.0 | \n",
" 0.400000 | \n",
" 0.000546 | \n",
"
\n",
" \n",
" 韶关 | \n",
" 151.0 | \n",
" 0.725962 | \n",
" 0.024946 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" 发展量 环比 渠道占比\n",
"分公司 \n",
"深圳 3647.0 0.967887 0.085430\n",
"广州 1469.0 1.034507 0.030841\n",
"佛山 263.0 1.091286 0.012738\n",
"东莞 6193.0 0.889671 0.268549\n",
"中山 1270.0 1.392544 0.091144\n",
"惠州 840.0 1.142857 0.075696\n",
"江门 48.0 0.578313 0.006345\n",
"珠海 445.0 0.882937 0.073724\n",
"汕头 10.0 0.588235 0.001327\n",
"揭阳 4.0 0.000000 0.000659\n",
"潮州 39.0 0.175676 0.006424\n",
"汕尾 7.0 0.583333 0.002309\n",
"湛江 13.0 1.444444 0.002500\n",
"茂名 8.0 0.888889 0.001870\n",
"阳江 4.0 0.800000 0.000576\n",
"云浮 1.0 0.250000 0.000397\n",
"肇庆 29.0 1.260870 0.005881\n",
"梅州 27.0 1.038462 0.004713\n",
"清远 32.0 1.684211 0.004692\n",
"河源 2.0 0.400000 0.000546\n",
"韶关 151.0 0.725962 0.024946"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#地市排序\n",
"dishi = ['深圳','广州','佛山','东莞',\n",
" '中山','惠州','江门','珠海',\n",
" '汕头','揭阳','潮州','汕尾',\n",
" '湛江','茂名','阳江','云浮',\n",
" '肇庆','梅州','清远','河源','韶关']\n",
"result.reindex(index=dishi).fillna(0)"
]
}
],
"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": "3.6.1"
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