斷崖式降溫，南方人過(guò)冬有多難？來(lái)看看取暖器銷(xiāo)量數(shù)據(jù)

#?導(dǎo)入工具包
import?numpy?as?np?
import?pandas?as?pd?

from?pyecharts.charts?import?Bar,?Pie,?Map,?Page
from?pyecharts?import?options?as?opts

import?jieba

#?讀取數(shù)據(jù)
df_all?=?pd.read_csv('../data/導(dǎo)出數(shù)據(jù).csv')
df_all.head()?

df_all.shape
(13212,?7)

• 刪除記錄的重復(fù)值
• goods_price列處理：提取數(shù)值
• purchase_num列處理：提取數(shù)值
• 計(jì)算銷(xiāo)售額sales_volume = goods_price*purchase_num
• 刪除多余的列

df?=?df_all.copy()
#?去除重復(fù)值
df.drop_duplicates(inplace=True)
df.shape
(6849,?7)

#?篩選記錄
df?=?df[df['purchase_num'].str.contains('人付款')]

#?goods_price列處理
df['goods_price']?=?df['goods_price'].str.extract('(\d+\.{0,1}\d*)')??
df['goods_price']?=?df['goods_price'].astype('float')

#?purchase_num列處理
df['num']?=?df['purchase_num'].str.extract('(\d+\.{0,1}\d*)')
df['num']?=?df['num'].astype('float')?
df['unit']?=?[10000?if?'萬(wàn)'?in?i?else?1?for?i?in?df['purchase_num']]

#?計(jì)算銷(xiāo)量
df['purchase_num']?=?df['num']?*?df['unit']

#?計(jì)算銷(xiāo)售額
df['sales_volume']?=?df['goods_price']?*?df['purchase_num']

#?提取省份字段?
df['province_name']?=?df['location'].astype('str').str.split('?').apply(lambda?x:x[0])?

#?刪除多余的列
df.drop(['num',?'unit',?'detail_url'],?axis=1,?inplace=True)

#?重置索引
df?=?df.reset_index(drop=True)
df.head()?

#?計(jì)算top10店鋪
shop_top10?=?df.groupby('shop_name')['purchase_num'].sum().sort_values(ascending=False).head(10)

#?計(jì)算銷(xiāo)量top10
province_top10?=?df.groupby('province_name')['purchase_num'].sum().sort_values(ascending=False).head(10)