Isin across 2 columns for groupby

Question

当我知道要在 df1 中匹配的数据将分布在 2 列（标题、ID）时，如何将 isin 与 or (?) 一起使用。

如果删除 ' 或 df1[df1.ID.isin(df2[column])] '

，则以下代码有效


import pandas as pd
df1 = pd.DataFrame({'Title': ['A1', 'A2', 'A3', 'C1', 'C2', 'C3'], 
                    'ID': ['B1', 'B2', 'B3', 'D1', 'D2', 'D3'], 
                    'Whole': ['full', 'full', 'full', 'semi', 'semi', 'semi']})

df2 = pd.DataFrame({'Group1': ['A1', 'A2', 'A3'], 
                    'Group2': ['B1', 'B2', 'B3']})

df = pd.DataFrame()

for column in df2.columns:
    
    d_group = (df1[df1.Title.isin(df2[column])] or df1[df1.ID.isin(df2[column])])
     
    df3 = d_group.groupby('Whole')['Whole'].count()\
                .rename(column, inplace=True)\
                .reindex(['part', 'full', 'semi'], fill_value='-')
    df = df.append(df3, ignore_index=False, sort=False)
        
print(df)

期望的输出：

            | full    | part     | semi
    --------+---------+----------+----------
    Group1  | 3       | -        | -
    Group2  | 3       | -        | -

Answer 1

您需要使用 | 而不是 or 并确保从您想要的 df 中正确使用 [] 到 sub-select。一般来说，符号是 df[selection_filter]

import pandas as pd
df1 = pd.DataFrame({'Title': ['A1', 'A2', 'A3', 'C1', 'C2', 'C3'],
                    'ID': ['B1', 'B2', 'B3', 'D1', 'D2', 'D3'],
                    'Whole': ['full', 'full', 'full', 'semi', 'semi', 'semi']})

df2 = pd.DataFrame({'Group1': ['A1', 'A2', 'A3'],
                    'Group2': ['B1', 'B2', 'B3']})

df = pd.DataFrame()

for column in df2.columns:

    d_group = df1[df1.Title.isin(df2[column]) | df1.ID.isin(df2[column])]

    df3 = d_group.groupby('Whole')['Whole'].count()\
                .rename(column, inplace=True)\
                .reindex(['part', 'full', 'semi'], fill_value='-')
    df = df.append(df3, ignore_index=False, sort=False)

print(df)

Isin across 2 columns for groupby

Isin across 2 columns for groupby

pandas

group-by

isin