小编pan*_*nda的帖子

我有以下数据框

import pandas as pd
import numpy as np
d = {

    'ID':[1,2,3,4,5,6],
    'Price1':[5,9,4,3,9,np.nan],
    'Price2':[9,10,13,14,18,np.nan],
    'Price3':[5,9,4,3,9,np.nan],
    'Price4':[9,10,13,14,18,np.nan],
    'Price5':[5,9,4,3,9,np.nan],
    'Price6':[np.nan,10,13,14,18,np.nan],
    'Price7':[np.nan,9,4,3,9,np.nan],
    'Price8':[np.nan,10,13,14,18,np.nan],
    'Price9':[5,9,4,3,9,np.nan],
    'Price10':[9,10,13,14,18,np.nan],
     'Type':['A','A','B','C','D','D'],


}
df = pd.DataFrame(data = d)
df

如何在价格 1 到价格 10 之间找到最大值并将其添加为新列？

以下数据帧是预期的输出。

import pandas as pd
import numpy as np
d = {

    'ID':[1,2,3,4,5,6],
    'Price1':[5,9,4,3,9,np.nan],
    'Price2':[9,10,13,14,18,np.nan],
    'Price3':[5,9,4,3,9,np.nan],
    'Price4':[9,10,13,14,18,np.nan],
    'Price5':[5,9,4,3,9,np.nan],
    'Price6':[np.nan,10,13,14,18,np.nan],
    'Price7':[np.nan,9,4,3,9,np.nan],
    'Price8':[np.nan,10,13,14,18,np.nan],
    'Price9':[5,9,4,3,9,np.nan],
    'Price10':[9,10,13,14,18,np.nan],
     'Type':['A','A','B','C','D','D'],
    'first_max':[9,10,13,14,18,np.nan],
    'two_max':[9,10,13,14,18,np.nan],
    'three_max':[9,10,13,14,18,np.nan],
    'four_max':[5,10,13,14,18,np.nan],
    'five_max':[5,10,13,14,18,np.nan],
    'six_max':[5,5,4,3,9,np.nan],
    'seven_max':[5,5,4,3,9,np.nan],
    'eight_max':[np.nan,5,4,3,9,np.nan],
    'nine_max':[np.nan,5,4,3,9,np.nan],
    'ten_max':[np.nan,5,4,3,9,np.nan],


}
df = pd.DataFrame(data = d)
pd.set_option('max_columns',25)
df

如何在价格 1 …

我有以下数据框

import pandas as pd
data=['5Star','FiveStar','five star','fiv estar']
data = pd.DataFrame(data,columns=["columnName"])

当我尝试使用一种条件进行过滤时，它工作正常。

data[data['columnName'].str.contains("5")]

输出：

    columnName
0   5Star

但是在处理多个条件时会出错。

如何过滤条件5和5？

预期输出：

    columnName
0   5Star
2   five star