I have a PySpark data frame with a string column(URL) and all records look in the following way

```
ID                                   URL
1          https://app.xyz.com/inboxes/136636/conversations/2686735685
2          https://app.xyz.com/inboxes/136636/conversations/2938415796
3          https://app.drift.com/inboxes/136636/conversations/2938419189

```

I want to basically extract the number after conversations/ from URL column using regex into another column.

I tried the following code but it doesn't give me any results.

```
df1 = df.withColumn('CONV_ID', split(convo_influ_new['URL'], '(?<=conversations/).*').getItem(0))

```

Expected:

```
ID                                   URL                                         CONV_ID
1          https://app.xyz.com/inboxes/136636/conversations/2686735685         2686735685
2          https://app.xyz.com/inboxes/136636/conversations/2938415796         2938415796     
3          https://app.drift.com/inboxes/136636/conversations/2938419189       2938419189

```

Result:

```
ID                                   URL                                         CONV_ID
1          https://app.xyz.com/inboxes/136636/conversations/2686735685         https://app.xyz.com/inboxes/136636/conversations/2686735685
2          https://app.xyz.com/inboxes/136636/conversations/2938415796         https://app.xyz.com/inboxes/136636/conversations/2938415796     
3          https://app.drift.com/inboxes/136636/conversations/2938419189       https://app.drift.com/inboxes/136636/conversations/2938419189

```

Not sure what's happening here. I tried the regex script in different online regex tester toolds and it highlights the part I want but never works in PySpark. I tried different PySpark functions like `f.split`, `regexp_extract`, `regexp_replace`, but none of them work.