Missing Values（缺失值）

缺失值之心里有数

import pandas as pd

data= pd.read_csv(r'G:\kaggle\melb_data.csv')

#统计缺失值的数量
missing_val_count_by_column= data.isnull().sum()
missing_val_count_by_column  #pandas Series类型

Suburb              0
Address             0
Rooms               0
Type                0
Price               0
Method              0
SellerG             0
Date                0
Distance            0
Postcode            0
Bedroom2            0
Bathroom            0
Car                62
Landsize            0
BuildingArea     6450
YearBuilt        5375
CouncilArea      1369
Lattitude           0
Longtitude          0
Regionname          0
Propertycount       0
dtype: int64

type(missing_val_count_by_column)

pandas.core.series.Series

#只输出有缺失值的
print(missing_val_count_by_column[missing_val_count_by_column > 0])

Car               62
BuildingArea    6450
YearBuilt       5375
CouncilArea     1369
dtype: int64

#判断data的'Car'列有缺失值吗？
data['Car'].isnull().any()  #该列有缺失值，则out：True

True

#看该列有多少个缺失值
data['Car'].isnull().sum()