Python 如何复制 pandas DataFrame 行并定期更改一列

将值添加到col_d x DataFrame.assign和numpy.tile列:

L = ['P','Q','R']
new_df = (pd.DataFrame(np.repeat(df.values, 3, axis=0), columns=df.columns)
           .assign(col_d = np.tile(L, len(df))))

print (new_df)
  col_acol_b col_c col_d
0       A1B1    C1     P
1       A1B1    C1     Q
2       A1B1    C1     R
3       A2B2    C2     P
4       A2B2    C2     Q
5       A2B2    C2     R
6       A3B3    C3     P
7       A3B3    C3     Q
8       A3B3    C3     R

另一个类似的 idea 是将索引和行重复DataFrame.loc次:

L = ['P','Q','R']
new_df = (df.loc[df.index.repeat(3)]
            .assign(col_d = np.tile(L, len(df)))
            .reset_index(drop=True))

print (new_df)
  col_acol_b col_c col_d
0       A1B1    C1     P
1       A1B1    C1     Q
2       A1B1    C1     R
3       A2B2    C2     P
4       A2B2    C2     Q
5       A2B2    C2     R
6       A3B3    C3     P
7       A3B3    C3     Q
8       A3B3    C3     R

编辑:

L = ['P','Q','R','S']
new_df = (pd.DataFrame(np.repeat(df.values, len(L), axis=0), columns=df.columns)
           .assign(col_d = np.tile(L, len(df)),
                   col_c = lambda x: x['col_c'].mask(x['col_d'].eq('S'), 'T')))

print (new_df)
   col_acol_b col_c col_d
0        A1B1    C1     P
1        A1B1    C1     Q
2        A1B1    C1     R
3        A1B1     T     S
4        A2B2    C2     P
5        A2B2    C2     Q
6        A2B2    C2     R
7        A2B2     T     S
8        A3B3    C3     P
9        A3B3    C3     Q
10       A3B3    C3     R
11       A3B3     T     S