How to count element in each list in the data frame with pandas?

Question

Given such a data frame df:

0     1
1     [12]
1     [13]
2     [11,12]
1     [10,0,1]
....

I'd like to count a certain value, for instance, '12' in each list of df. So i tried:

df.apply(list.count('12'))

but got error: TypeError: descriptor 'count' requires a 'list' object but received a 'str'. But they are exactly lists in df[1]! How can I correct it? Thanks!

Answer 1

I think you can try first select column as Series by ix and then apply function x.count(12):

import pandas as pd

d = { 0:pd.Series([1,1,2,1]),
      1:pd.Series([[12], [13], [11,12 ],[10,0,1]])}

df = pd.DataFrame(d)  

print df 
   0           1
0  1        [12]
1  1        [13]
2  2    [11, 12]
3  1  [10, 0, 1]

print df.ix[:, 1]
0          [12]
1          [13]
2      [11, 12]
3    [10, 0, 1]
Name: 1, dtype: object

print df.ix[:, 1].apply(lambda x: x.count(12))   
0    1
1    0
2    1
3    0
Name: 1, dtype: int64

Or use iloc for selecting:

print df.iloc[:, 1].apply(lambda x: x.count(12))   
0    1
1    0
2    1
3    0
Name: 1, dtype: int64

EDIT:

I think column 1 contains NaN.

You can use:

print df 
   0           1
0  1         NaN
1  1        [13]
2  2    [11, 12]
3  1  [10, 0, 1]

print df.ix[:, 1].notnull()
0    False
1     True
2     True
3     True
Name: 1, dtype: bool

print df.ix[df.ix[:, 1].notnull(), 1].apply(lambda x: x.count(12))   
1    0
2    1
3    0
Name: 1, dtype: int64

EDIT2:

If you want filter by index (e.g. 0:2) and by NaN in column 1:

print df 
   0           1
0  1         NaN
1  1        [13]
2  2    [11, 12]
3  1  [10, 0, 1]

#filter df by index - only 0 to 2 
print df.ix[0:2, 1]
0         NaN
1        [13]
2    [11, 12]
Name: 1, dtype: object

#boolean series, where is not nul filtered df
print df.ix[0:2, 1].notnull()
0    False
1     True
2     True
Name: 1, dtype: bool

#get column 1: first is filtered to 0:2 index and then if is not null
print df.ix[0:2, 1][df.ix[0:2, 1].notnull()]
1        [13]
2    [11, 12]
Name: 1, dtype: object

#same as above, but more nice
df1 =  df.ix[0:2, 1]
print df1
0         NaN
1        [13]
2    [11, 12]
Name: 1, dtype: object

print df1[df1.notnull()]
1        [13]
2    [11, 12]
Name: 1, dtype: object

#apply count
print df1[df1.notnull()].apply(lambda x: x.count(12))   
1    0
2    1
Name: 1, dtype: int64