缺失值

使用 pandas 进行数据处理

Maggie Matsui

Senior Content Developer at DataCamp

什么是缺失值？

Name	Breed	Color	Height (cm)	Weight (kg)	Date of Birth
Bella	Labrador	Brown	56	25	2013-07-01
Charlie	Poodle	Black	43	23	2016-09-16
Lucy	Chow Chow	Brown	46	22	2014-08-25
Cooper	Schnauzer	Gray	49	17	2011-12-11
Max	Labrador	Black	59	29	2017-01-20
Stella	Chihuahua	Tan	18	2	2015-04-20
Bernie	St. Bernard	White	77	74	2018-02-27

什么是缺失值？

Name	Breed	Color	Height (cm)	Weight (kg)	Date of Birth
Bella	Labrador	Brown	56	?	2013-07-01
Charlie	Poodle	Black	43	23	2016-09-16
Lucy	Chow Chow	Brown	46	22	2014-08-25
Cooper	Schnauzer	Gray	49	?	2011-12-11
Max	Labrador	Black	59	29	2017-01-20
Stella	Chihuahua	Tan	18	2	2015-04-20
Bernie	St. Bernard	White	77	74	2018-02-27

pandas DataFrame 中的缺失值

print(dogs)

      name        breed  color  height_cm  weight_kg date_of_birth
0    Bella     Labrador  Brown         56        NaN    2013-07-01
1  Charlie       Poodle  Black         43       24.0    2016-09-16
2     Lucy    Chow Chow  Brown         46       24.0    2014-08-25
3   Cooper    Schnauzer   Gray         49        NaN    2011-12-11
4      Max     Labrador  Black         59       29.0    2017-01-20
5   Stella    Chihuahua    Tan         18        2.0    2015-04-20
6   Bernie  St. Bernard  White         77       74.0    2018-02-27

检测缺失值

dogs.isna()

    name  breed  color  height_cm  weight_kg  date_of_birth
0  False  False  False      False       True          False
1  False  False  False      False      False          False
2  False  False  False      False      False          False
3  False  False  False      False       True          False
4  False  False  False      False      False          False
5  False  False  False      False      False          False
6  False  False  False      False      False          False

检测是否存在缺失

dogs.isna().any()

name             False
breed            False
color            False
height_cm        False
weight_kg         True
date_of_birth    False
dtype: bool

统计缺失值

dogs.isna().sum()

name             0
breed            0
color            0
height_cm        0
weight_kg        2
date_of_birth    0
dtype: int64

可视化缺失值

import matplotlib.pyplot as plt

dogs.isna().sum().plot(kind="bar")
plt.show()

一个柱状图，统计 dogs 数据集中各列的缺失值数量。除 weight 外均为 0，weight 有两个缺失值。

删除缺失值

dogs.dropna()

      name        breed  color  height_cm  weight_kg date_of_birth
1  Charlie       Poodle  Black         43       24.0    2016-09-16
2     Lucy    Chow Chow  Brown         46       24.0    2014-08-25
4      Max     Labrador  Black         59       29.0    2017-01-20
5   Stella    Chihuahua    Tan         18        2.0    2015-04-20
6   Bernie  St. Bernard  White         77       74.0    2018-02-27

替换缺失值

dogs.fillna(0)

      name        breed  color  height_cm  weight_kg date_of_birth
0    Bella     Labrador  Brown         56        0.0    2013-07-01
1  Charlie       Poodle  Black         43       24.0    2016-09-16
2     Lucy    Chow Chow  Brown         46       24.0    2014-08-25
3   Cooper    Schnauzer   Gray         49        0.0    2011-12-11
4      Max     Labrador  Black         59       29.0    2017-01-20
5   Stella    Chihuahua    Tan         18        2.0    2015-04-20
6   Bernie  St. Bernard  White         77       74.0    2018-02-27

Passons à la pratique !

使用 pandas 进行数据处理