如何根据 pandas 中的条件映射两行不同的数据框 [英] how to map two rows of different dataframe based on a condition in pandas

问题描述

我有两个数据框

df1，

 Names
 one two three
 Sri is a good player
 Ravi is a mentor
 Kumar is a cricketer player

df2，

 values
 sri
 NaN
 sri, is
 kumar,cricketer player

我正在尝试在df1中获取包含df2中所有项目的行

I am trying to get the row in df1 which contains the all the items in df2

我的预期输出是

 values                  Names
 sri                     Sri is a good player
 NaN
 sri, is                 Sri is a good player
 kumar,cricketer player  Kumar is a cricketer player

我尝试了，df1["Names"].str.contains("|".join(df2["values"].values.tolist())) 我也尝试过，

i tried, df1["Names"].str.contains("|".join(df2["values"].values.tolist())) I also tried,

但是我无法达到预期的输出，因为它具有(，").请帮助

but I cannot achieve my expected output as it has (","). Please help

推荐答案

在Numpy广播中使用集合逻辑.

Using set logic with Numpy broadcasting.

d1 = df1['Names'].fillna('').str.lower().str.split('[^a-z]+').apply(set).values
d2 = df2['values'].fillna('').str.lower().str.split('[^a-z]+').apply(set).values

i, j = np.where(d1 >= d2[:, None])

df2.assign(Names=pd.Series(df1['Names'].values[j], df2['values'].index[i]))

                   values                        Names
0                     sri         Sri is a good player
1                     NaN                          NaN
2                 sri, is         Sri is a good player
3  kumar,cricketer player  Kumar is a cricketer player

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