pandas dataframe 赋值操作2

import pandas as pd
import numpy as np

pandas dataframe 赋值操作2

df = pd.read_csv('data/employee_sample.csv',index_col=0)
df

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df['BONUS RATE'] = [.2, .1, .13, .15, .12, .3, .05]
df

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• 根据salary 与bonusrate 计算bonus并且增加bonus列

df['bonus']=df['SALARY']*df['BONUS RATE']
df

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• 修改所有的bonus为10000
  • 方式1：

df['bonus']=10000

df

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- 方式2：

df.loc[:,'bonus']=9999

df

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• 修改YEARS EXPERIENCE数据类型

df['YEARS EXPERIENCE'].dtype

dtype('int64')

df['YEARS EXPERIENCE']=df['YEARS EXPERIENCE'].astype('object')

df['YEARS EXPERIENCE']

Tom         23
Niko         1
Penelope    12
Aria         8
Sofia       23
Dean         3
Zach         4
Name: YEARS EXPERIENCE, dtype: object

df['YEARS EXPERIENCE'].dtype

dtype('O')

+ 给bonus列的['Niko', 'Penelope', 'Aria'] 赋值

df.loc[['Niko', 'Penelope', 'Aria'],'bonus']=[2301,4563,6548]

df

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• 使用iloc 赋值

df.iloc[3:6,3]=10

df

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df.iloc[:,3]=33
df

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+ 使用loc 筛选数据并修改其值
    - 修改DEPARTMENT列中等于Engineering，对应的bonus值

df.loc[df['DEPARTMENT']=='Engineering','bonus']+=500

df

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Series 赋值操作

s=df['SALARY'].copy()
s

Tom         107962
Niko         30347
Penelope     60258
Aria         43618
Sofia        26125
Dean         33592
Zach         37565
Name: SALARY, dtype: int64

s.loc[['Tom','Niko','Aria']]=[99,123,321]

s

Tom            99
Niko          123
Penelope       33
Aria          321
Sofia       26125
Dean        33592
Zach        37565
Name: SALARY, dtype: int64

s.iloc[1:3]=33

s

Tom            99
Niko           33
Penelope       33
Aria           99
Sofia       26125
Dean        33592
Zach        37565
Name: SALARY, dtype: int64