DataFrame index 操作

import pandas as pd
import numpy as np

DataFrame index 操作

df= pd.read_csv('data/sample_data2.csv')

df

	Names	state	color	food	age	height	score
0	Jane	NY	blue	Steak	30	165	4.6
1	Niko	TX	green	Lamb	2	70	8.3
2	Aaron	FL	red	Mango	12	120	9.0
3	Penelope	AL	white	Apple	4	80	3.3
4	Dean	AK	gray	Cheese	32	180	1.8
5	Christina	TX	black	Melon	33	172	9.5
6	Cornelia	TX	red	Beans	69	150	2.2

上边df 使用的是默认的index，该索引为 RangeIndex 类型 如下

df.index

RangeIndex(start=0, stop=7, step=1)

• 将dataframe 某一列设置为索引

df2_index = df.set_index('Names')

df2_index

	state	color	food	age	height	score
Names
Jane	NY	blue	Steak	30	165	4.6
Niko	TX	green	Lamb	2	70	8.3
Aaron	FL	red	Mango	12	120	9.0
Penelope	AL	white	Apple	4	80	3.3
Dean	AK	gray	Cheese	32	180	1.8
Christina	TX	black	Melon	33	172	9.5
Cornelia	TX	red	Beans	69	150	2.2

df

	Names	state	color	food	age	height	score
0	Jane	NY	blue	Steak	30	165	4.6
1	Niko	TX	green	Lamb	2	70	8.3
2	Aaron	FL	red	Mango	12	120	9.0
3	Penelope	AL	white	Apple	4	80	3.3
4	Dean	AK	gray	Cheese	32	180	1.8
5	Christina	TX	black	Melon	33	172	9.5
6	Cornelia	TX	red	Beans	69	150	2.2

上边默认是返回个新的dataframe，原来的不变

df.set_index('Names',inplace=True)

df

	state	color	food	age	height	score
Names
Jane	NY	blue	Steak	30	165	4.6
Niko	TX	green	Lamb	2	70	8.3
Aaron	FL	red	Mango	12	120	9.0
Penelope	AL	white	Apple	4	80	3.3
Dean	AK	gray	Cheese	32	180	1.8
Christina	TX	black	Melon	33	172	9.5
Cornelia	TX	red	Beans	69	150	2.2

在原来基础上修改inplace=True

• 下面查看行索引 index 的名字

df.index.name

'Names'

• 查看行索引 内容值

df.index

Index(['Jane', 'Niko', 'Aaron', 'Penelope', 'Dean', 'Christina', 'Cornelia'], dtype='object', name='Names')

• 重置行索引为默认索引，生成新的Dataframe

df_rev=df.reset_index()
df_rev

	Names	state	color	food	age	height	score
0	Jane	NY	blue	Steak	30	165	4.6
1	Niko	TX	green	Lamb	2	70	8.3
2	Aaron	FL	red	Mango	12	120	9.0
3	Penelope	AL	white	Apple	4	80	3.3
4	Dean	AK	gray	Cheese	32	180	1.8
5	Christina	TX	black	Melon	33	172	9.5
6	Cornelia	TX	red	Beans	69	150	2.2

将行索引还原成默认的，names还原成列

df

	state	color	food	age	height	score
Names
Jane	NY	blue	Steak	30	165	4.6
Niko	TX	green	Lamb	2	70	8.3
Aaron	FL	red	Mango	12	120	9.0
Penelope	AL	white	Apple	4	80	3.3
Dean	AK	gray	Cheese	32	180	1.8
Christina	TX	black	Melon	33	172	9.5
Cornelia	TX	red	Beans	69	150	2.2

• 在原来Df基础上修改

df.reset_index(inplace=True)

df

	Names	state	color	food	age	height	score
0	Jane	NY	blue	Steak	30	165	4.6
1	Niko	TX	green	Lamb	2	70	8.3
2	Aaron	FL	red	Mango	12	120	9.0
3	Penelope	AL	white	Apple	4	80	3.3
4	Dean	AK	gray	Cheese	32	180	1.8
5	Christina	TX	black	Melon	33	172	9.5
6	Cornelia	TX	red	Beans	69	150	2.2

• 行索引重新命名

df2_index

	state	color	food	age	height	score
Names
Jane	NY	blue	Steak	30	165	4.6
Niko	TX	green	Lamb	2	70	8.3
Aaron	FL	red	Mango	12	120	9.0
Penelope	AL	white	Apple	4	80	3.3
Dean	AK	gray	Cheese	32	180	1.8
Christina	TX	black	Melon	33	172	9.5
Cornelia	TX	red	Beans	69	150	2.2

• 给行索引重命名后后返回新的行索引

df2_index.index.rename('AllNames')

Index(['Jane', 'Niko', 'Aaron', 'Penelope', 'Dean', 'Christina', 'Cornelia'], dtype='object', name='AllNames')

df2_index

	state	color	food	age	height	score
Names
Jane	NY	blue	Steak	30	165	4.6
Niko	TX	green	Lamb	2	70	8.3
Aaron	FL	red	Mango	12	120	9.0
Penelope	AL	white	Apple	4	80	3.3
Dean	AK	gray	Cheese	32	180	1.8
Christina	TX	black	Melon	33	172	9.5
Cornelia	TX	red	Beans	69	150	2.2

• 使用重命名后新生成的行索引，修改行索引

df2_index.index = df2_index.index.rename('AllNames')

df2_index

	state	color	food	age	height	score
AllNames
Jane	NY	blue	Steak	30	165	4.6
Niko	TX	green	Lamb	2	70	8.3
Aaron	FL	red	Mango	12	120	9.0
Penelope	AL	white	Apple	4	80	3.3
Dean	AK	gray	Cheese	32	180	1.8
Christina	TX	black	Melon	33	172	9.5
Cornelia	TX	red	Beans	69	150	2.2

• 修改行索引内容

n_index=['Jane1','Niko1','Aaron1','Penelope1','Dean1','Christina1','Cornelia1']

df2_index.index= n_index

df2_index

	state	color	food	age	height	score
Jane1	NY	blue	Steak	30	165	4.6
Niko1	TX	green	Lamb	2	70	8.3
Aaron1	FL	red	Mango	12	120	9.0
Penelope1	AL	white	Apple	4	80	3.3
Dean1	AK	gray	Cheese	32	180	1.8
Christina1	TX	black	Melon	33	172	9.5
Cornelia1	TX	red	Beans	69	150	2.2

• 使用.属性的方式 访问列索引

df2_index.score

Jane1         4.6
Niko1         8.3
Aaron1        9.0
Penelope1     3.3
Dean1         1.8
Christina1    9.5
Cornelia1     2.2
Name: score, dtype: float64

df2_index.food

Jane1          Steak
Niko1           Lamb
Aaron1         Mango
Penelope1      Apple
Dean1         Cheese
Christina1     Melon
Cornelia1      Beans
Name: food, dtype: object

df2_index.food.Niko1

'Lamb'

此方式访问可以点出对应的方法，方便

df2_index[['food','food','food']]

	food	food	food
Jane1	Steak	Steak	Steak
Niko1	Lamb	Lamb	Lamb
Aaron1	Mango	Mango	Mango
Penelope1	Apple	Apple	Apple
Dean1	Cheese	Cheese	Cheese
Christina1	Melon	Melon	Melon
Cornelia1	Beans	Beans	Beans