一个单元格的字符串值在 pandas 数据帧的其他列中重复了多少次？

Question

I am trying to find out the number of times each cell value of column A appears in all the cells of the other column B using pandas. for example for cell A1 value, we need to vlookup its value in all cells of column B and to find out in how many cells of column B it's repeated and then put the count value against it in the column C. I checked all the possible solutions such as using contains, extract, groupby, etc but no result. also, the value in the B column has no special text pattern to can define it in the code.

This is what I've as a data frame:

      A                            B                                C
 ============  ===============================================  ========
   T4561                                      T4561 (KHO ZAD)
   E2962                     E2962 (Bat - Rouchan),T5362(asw)
  DT2172                 T2172 (Masd),T2117 (Masd),T4561(fsd)
   T6096              T6096 (Mara),H1005 (BAHH), H1049 (QIEH)
   T5362                 T5362 (SYMI (ABAI)),E0993,E7523(pwd)
   E0993                       E0993 (Tean),T4561,E0993(ssdc)
   E1834                        E1834 (Ahaz),T5362,E0993(sdw)
   T2844  T2844 (Varmn),T3798 (QASIN), T3596 (Vara),T4561(qw)
   E7523                              E7523 (Sabk),E0993(bbz)
   T9062                        T9062 (Shrz),T5362,E7523(fgf)

And this is what I need:

      A                            B                                C
 ============  ===============================================  ========
       T4561                                      T4561 (KHO ZAD)  4
       E2962                     E2962 (Bat - Rouchan),T5362(asw)  1
      DT2172                 T2172 (Masd),T2117 (Masd),T4561(fsd)  0
       T6096              T6096 (Mara),H1005 (BAHH), H1049 (QIEH)  1
       T5362                 T5362 (SYMI (ABAI)),E0993,E7523(pwd)  4
       E0993                       E0993 (Tean),T4561,E0993(ssdc)  5
       E1834                        E1834 (Ahaz),T5362,E0993(sdw)  1
       T2844  T2844 (Varmn),T3798 (QASIN), T3596 (Vara),T4561(qw)  1
       E7523                              E7523 (Sabk),E0993(bbz)  3
       T9062                        T9062 (Shrz),T5362,E7523(fgf)  1

Answer 1

Use Series.str.extractall along with the regex pattern, then use Series.value_counts to compute the frequency, then use Series.map to map the values in column A to their corresponding frequencies:

m = df['B'].str.extractall(f"({'|'.join(df['A'])})")[0].value_counts()
df['C'] = df['A'].map(m).fillna(0)

Result:

        A                                                    B    C
0   T4561                                      T4561 (KHO ZAD)  4.0
1   E2962                     E2962 (Bat - Rouchan),T5362(asw)  1.0
2  DT2172                 T2172 (Masd),T2117 (Masd),T4561(fsd)  0.0
3   T6096              T6096 (Mara),H1005 (BAHH), H1049 (QIEH)  1.0
4   T5362                 T5362 (SYMI (ABAI)),E0993,E7523(pwd)  4.0
5   E0993                       E0993 (Tean),T4561,E0993(ssdc)  5.0
6   E1834                        E1834 (Ahaz),T5362,E0993(sdw)  1.0
7   T2844  T2844 (Varmn),T3798 (QASIN), T3596 (Vara),T4561(qw)  1.0
8   E7523                              E7523 (Sabk),E0993(bbz)  3.0
9   T9062                        T9062 (Shrz),T5362,E7523(fgf)  1.0