在Pandas中更改DataFrame中的值

import pandas as pd
import numpy as np
dates = pd.date_range('20200315', periods = 5)
df = pd.DataFrame(np.arange(20).reshape((5,4)), index = dates, columns = ['A','B','C','D'])
print(df)
#输出
             A   B   C   D
2020-03-15   0   1   2   3
2020-03-16   4   5   6   7
2020-03-17   8   9  10  11
2020-03-18  12  13  14  15
2020-03-19  16  17  18  19

df.loc['20200318','C'] = 20200318     #标签索引
df.iloc[2,3] = 20200318    #数字索引
print(df)
#输出
             A   B         C         D
2020-03-15   0   1         2         3
2020-03-16   4   5         6         7
2020-03-17   8   9        10  20200318
2020-03-18  12  13  20200318        15
2020-03-19  16  17        18        19

df.B[df.C>6] = 0    #C字段中大于6的那些行在B字段中全都设为0
print(df)
#输出
             A  B         C         D
2020-03-15   0  1         2         3
2020-03-16   4  5         6         7
2020-03-17   8  0        10  20200318
2020-03-18  12  0  20200318        15
2020-03-19  16  0        18        19

df['E'] = np.nan
print(df)
#输出
             A   B   C   D   E
2020-03-15   0   1   2   3 NaN
2020-03-16   4   5   6   7 NaN
2020-03-17   8   9  10  11 NaN
2020-03-18  12  13  14  15 NaN
2020-03-19  16  17  18  19 NaN

df['F'] = pd.Series([11,22,33,44,55],index = pd.date_range('20200315',periods = 5))
print(df)
#输出
             A   B   C   D   E   F
2020-03-15   0   1   2   3 NaN  11
2020-03-16   4   5   6   7 NaN  22
2020-03-17   8   9  10  11 NaN  33
2020-03-18  12  13  14  15 NaN  44
2020-03-19  16  17  18  19 NaN  55

import pandas as pd
data = pd.read_excel('some_chaneg.xlsx')
data1 = data
data1.iloc[2:5,3:] = 0
data1

Series.where(cond, other=nan, inplace=False, axis=None, level=None, errors='rais',...)

# data2为data数据的一部分
data2 = data.iloc[0:,1:]
print(data2)
data2.where(data2>25, data2+5,inplace=True)

mask(cond, other=nan)

data2.mask(data2<25, data2+5, inplace=True)

# 替换文本值
data3 = data
data3.replace('wange', 'sheng', inplace=True)
data3

# 替换多个值# 将所有的0和1互换data3.replace({<!-- -->1:0,0:1},inplace&#61;True)
# 替换多个值
# 将所有的0和1互换
data3.replace({1:0,0:1},inplace=True)

# 切记使用正则表达式的时候,一定要添加上regex=True
data3.replace('[a-zA-Z]+','Anonymous',regex=True,inplace=True)