A subset of my dataset looks as follows where cells in "cat1_ids" column contains list of "cat1" categories and cells in "person_id_list" column contains list of persons id. There are 2000 "cat1" categories and 1500 person, How to prove "no_of_days" is related to to these two columns? After proving a relationship exists the next step is to train a model on this data for predicting "no_of_days". Any suggestions on how to deal with cells containing tuple of values? (both graphical and statistical methods would be appreciated for proving relationship)

  cat1_ids    person_id_list   no_of_days
0   (602,)        (12713,)        1.727083
4   (3, 131)      (12408,)        1.770833
5   (13,)         (12404,)        0.592361
6   (442,)        (12327,)        2.518750
7   (761,)        (12720,)        7.601389

shape => 75000x3

Edit: combinations of cat1_ids has greater influence on no_of_days as compared to person_id_list (it's domain knowledge).

A subset of my dataset looks as follows where cells in "cat1_ids" column contains list of "cat1" categories and cells in "person_id_list" column contains list of persons id. There are 2000 "cat1" categories and 1500 person, How to prove "no_of_days" is related to to these two columns? After proving a relationship exists the next step is to train a model on this data for predicting "no_of_days". Any suggestions on how to deal with cells containing tuple of values and make a model on it? (both graphical and statistical methods would be appreciated for proving relationship)

  cat1_ids    person_id_list   no_of_days
0   (602,)        (12713,)        1.727083
4   (3, 131)      (12408,)        1.770833
5   (13,)         (12404,)        0.592361
6   (442,)        (12327,)        2.518750
7   (761,)        (12720,)        7.601389

shape => 75000x3

Which model should i use to train over this data to make prediction for no_of_days?

Edit: combinations of cat1_ids has greater influence on no_of_days as compared to person_id_list (it's domain knowledge). Max length of cat_ids and person_id_list is 8.

A subset of my dataset looks as follows where cells in "cat1_ids" column contains list of "cat1" categories and cells in "person_id_list" column contains list of persons id. There are 2000 "cat1" categories and 1500 person, How to prove "no_of_days" is related to to these two columns? After proving a relationship exists the next step is to train a model on this data for predicting "no_of_days". Any suggestions on how to deal with cells containing tuple of values? (both graphical and statistical methods would be appreciated for proving relationship)

  cat1_ids    person_id_list   no_of_days
0   (602,)        (12713,)        1.727083
4   (3, 131)      (12408,)        1.770833
5   (13,)         (12404,)        0.592361
6   (442,)        (12327,)        2.518750
7   (761,)        (12720,)        7.601389

shape => 75000x3

A subset of my dataset looks as follows where cells in "cat1_ids" column contains list of "cat1" categories and cells in "person_id_list" column contains list of persons id. There are 2000 "cat1" categories and 1500 person, How to prove "no_of_days" is related to to these two columns? After proving a relationship exists the next step is to train a model on this data for predicting "no_of_days". Any suggestions on how to deal with cells containing tuple of values? (both graphical and statistical methods would be appreciated for proving relationship)

  cat1_ids    person_id_list   no_of_days
0   (602,)        (12713,)        1.727083
4   (3, 131)      (12408,)        1.770833
5   (13,)         (12404,)        0.592361
6   (442,)        (12327,)        2.518750
7   (761,)        (12720,)        7.601389

shape => 75000x3

Edit: combinations of cat1_ids has greater influence on no_of_days as compared to person_id_list (it's domain knowledge).