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Match the string data inside a group - Pandas

I have dataframe like this:

+--------+------------+----------+--------------+--------------+----------------+--------------+--------------+
| company|          id|ann_rtn_dt|share_class_nb|shrhldr_seq_nb|shrhldr_first_nm|shrhldr_mid_nm|shrhldr_sur_nm|
+--------+------------+----------+--------------+--------------+----------------+--------------+--------------+
|SYNTHE01|SYNTHE01_1_1|2022-11-28|             1|             1|            NIEL|        ANDREW|        HOPSON|
|SYNTHE01|SYNTHE01_3_1|2022-11-28|             3|             1|          NICOLE|        CLAIRE|          MORE|
|SYNTHE01|SYNTHE01_1_2|2022-11-28|             1|             2|               N|             C|          MORE|
|SYNTHE01|SYNTHE01_2_1|2022-11-28|             2|             1|            NEIL|        ANDREW|        HOPSON|
|SYNTHE01|SYNTHE01_3_1|2022-11-28|             3|             1|          NICOLE|        CLAIRE|          MORE|
|SYNTHE02|SYNTHE02_1_1|2022-11-28|             1|             1|            MIKE|              |        LOPSON|
|SYNTHE02|SYNTHE02_3_1|2022-11-28|             3|             1|          NIMIKE|              |        LOPSON|
|SYNTHE02|SYNTHE02_1_2|2022-11-28|             1|             2|            MIKE|              |        LOPSON|
|SYNTHE02|SYNTHE02_2_1|2022-11-28|             2|             1|            MIKE|              |        LOPSON|
+--------+------------+----------+--------------+--------------+----------------+--------------+--------------+

The whole dataframe can be grouped 2 distinct company column i.e. SYNTE01 and SYNTHE02.

My use case is to do matching inside the company.

STATUS_1 is set to min of id, when there is full match of shrhldr_first_nm, shrhldr_mid_nm and shrhldr_sur_nm in the grouop.

STATUS_2 is set to min of id, when there is match of first byte of shrhldr_first_nm and shrhldr_mid_nm in the group. And shrhldr_sur_nm matches exactly.

For eg. in COMPANY SYNTHE01, NIEL ANDREW HOPSON in row1 matches with NIEL ANDREW HOPSON in row4. The column STATUS_1 is set to min of id column for both.

For eg. in COMPANY SYNTHE01, the first byte of NICOLE CLAIRE MORE in row2 matches with N C More in row3. The column STATUS_2 is set to min of id column for both.

My output dataframe would look like below:

+--------+------------+----------+--------------+--------------+----------------+--------------+--------------+-------------+-------------+
| company|          id|ann_rtn_dt|share_class_nb|shrhldr_seq_nb|shrhldr_first_nm|shrhldr_mid_nm|shrhldr_sur_nm|     STATUS_1|     STATUS_2|
+--------+------------+----------+--------------+--------------+----------------+--------------+--------------+-------------+-------------+
|SYNTHE01|SYNTHE01_1_1|2022-11-28|             1|             1|            NIEL|        ANDREW|        HOPSON| SYNTHE01_1_1|             |
|SYNTHE01|SYNTHE01_3_1|2022-11-28|             3|             1|          NICOLE|        CLAIRE|          MORE| SYNTHE01_3_1| SYNTHE01_1_2|
|SYNTHE01|SYNTHE01_1_2|2022-11-28|             1|             2|               N|             C|          MORE|             | SYNTHE01_1_2|
|SYNTHE01|SYNTHE01_2_1|2022-11-28|             2|             1|            NEIL|        ANDREW|        HOPSON| SYNTHE01_1_1|             |
|SYNTHE01|SYNTHE01_3_2|2022-11-28|             3|             1|          NICOLE|        CLAIRE|          MORE| SYNTHE01_3_1| SYNTHE01_1_2|
|SYNTHE02|SYNTHE02_1_1|2022-11-28|             1|             1|            MIKE|              |        LOPSON| SYNTHE02_1_1|             |
|SYNTHE02|SYNTHE02_3_1|2022-11-28|             3|             1|          NIMIKE|              |        LOPSON|             |             |
|SYNTHE02|SYNTHE02_1_2|2022-11-28|             1|             2|            MIKE|              |        LOPSON| SYNTHE02_1_1|             |
|SYNTHE02|SYNTHE02_2_1|2022-11-28|             2|             1|            MIKE|              |        LOPSON| SYNTHE02_1_1|             |
+--------+------------+----------+--------------+--------------+----------------+--------------+--------------+-------------+-------------+

We tried this in Pyspark, could not achieve it. We are now trying to do it in Pandas. Please suggest any possible approach. Thank you.



source https://stackoverflow.com/questions/76256407/match-the-string-data-inside-a-group-pandas
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