Python的pandas库的用法（五）处理丢失数据

import pandas as pd
import numpy as np

dates = pd.date_range('20190101',periods=6)
df = pd.DataFrame(np.arange(24).reshape((6,4)),index=dates,columns=['A','B','C','D'])
df.iloc[0,1] = np.nan
df.iloc[1,2] = np.nan

print(df)

选择丢掉数据缺失的某行或某列

# axis = 0 按行来dorp
print(df.dropna(axis=0,how ='any')) # 有任何nan就丢掉

# axis = 1 按列来drop
print(df.dropna(axis=1,how='any')) # how={‘any’，‘all’} 默认how='any'

print(df.dropna(axis=0,how='all')) 

填充缺失数据

print(df)
print(df.fillna(value=0))

检查是否缺失数据

print(df.isnull()) # 缺值的返回True，否则返回False

如果DataFrame里数据很多怎么判断是否缺值？

print(np.any(df.isnull())==True)

# 至少包含一个缺失值时返回Ture