Python处理数据利器 → Pandas
数据一般格式:csv/xlsx
如何用pandas读取数据
案例:用pandas处理商铺数据
用pandas处理
导入模块
import pandas as pd # 导入pandas模块 import warnings warnings.filterwarnings('ignore') # 不发出警告 print('成功导入模块')
# 如何用pandas读取数据 - csv df = pd.read_csv('/home/kesci/商铺数据.csv') print(type(df),df['name'].dtype) # 查看df类型,查看df中一列的数值类型 df.head()
# 用pandas处理商铺数据 - comment字段清洗 df1 = df[df['comment'].str.contains('条')] df1['comment'] = df1['comment'].str.split('条').str[0] print(df1['comment'].dtype) df1['comment'] = df1['comment'].astype('int') print(df1['comment'].dtype) # 更改列数值类型 df1.head()
# 用pandas处理商铺数据 - price字段清洗 df1 = df1[df1['price'].str.contains('¥')] df1['price'] = df1['price'].str.split('¥').str[-1] df1['price'] = df1['price'].astype('float') print(df1['price'].dtype) # 更改列数值类型 df1.head()
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