CODEWITHSUNDEEP
pandascount
Nadiia
Nadiia

Reputation: 217

Count of the occurrence in the list for a given value

I have a data frame which has ids, some code value,code_name and a list_of_ids is a list of ids .

id code   code_name  list_of_ids
1  AB111  apple      [5,2,3,4]
2  AB222  pear       [3,4]
3  AB333  banana     [1]
4  AB111  apple      []
5  AB222  pear       [2,6,4]
6  AB333  banana     [1,3,5]
7  AB333  banana     [1,3,6]

I'm trying to get a count of ids from the list_of_ids where id from the list has the same code_name as a value in id column.

Thanks. The desired output is to get the count. Column for_explanation is added to display only

id code   code_name  for_explanation            count
1  AB111  apple      [pear,pear,banana,apple]   1
2  AB222  pear       [banana,apple]             0
3  AB333  banana     [apple]                    0
4  AB111  apple      []                         0
5  AB222  pear       [pear,banana,apple]        0
6  AB333  banana     [apple,banana,pear]        0
7  AB333  banana     [apple,banana,banana]      2

Upvotes: 0

Views: 24

Answers (1)

mozway
mozway

Reputation: 260390

You can use a list comprehension:

s = df.set_index('id')['code_name']

df['count'] = [sum(1 for i in l if s.get(i)==c)
               for c,l in zip(df['code_name'], df['list_of_ids'])]

Or explode and groupby:

s = df.set_index('id')['code_name']

df['count'] = (df
   .explode('list_of_ids')
   .groupby(level=0)
   .apply(lambda d: d['list_of_ids'].map(s).eq(d['code_name']).sum())
)

output:

   id   code code_name   list_of_ids  count
0   1  AB111     apple  [5, 2, 3, 4]      1
1   2  AB222      pear        [3, 4]      0
2   3  AB333    banana           [1]      0
3   4  AB111     apple            []      0
4   5  AB222      pear     [2, 6, 4]      1
5   6  AB333    banana     [1, 3, 5]      1
6   7  AB333    banana     [1, 3, 6]      2

Upvotes: 1

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