python remove zero values from column in dataframe-CodePudding

I have a dataframe (df) that has two columns (samples, results)

df = pd.DataFrame({'samples': ['sample_1', 'sample_2', 'sample_3', 'sample_4', 'sample_5'],
                   'results': [[0.0,0.0,2.0,0.0,0.0,2.0,0.0,3.0,3.0],
                              [1.0,3.0,1.0,1.0,1.0,3.0,1.0,0.0,1.0],
                              [0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0],
                              [1.0,0.0,1.0,1.0,1.0,0.0,1.0,0.0,1.0],
                              [0.0,0.0,0.0,0.0,3.0,0.0,0.0,3.0,0.0]]})

I applied function (f) to calculate the count of each value, e.g. for sample_1, we have 5 numbers of (0), zero number of 1, two numbers of 2 and 3. For sample_2, we have 1 number of (0), 6 number of 1, zero number of 2 and 2 number of 3, etc.

from collections import Counter

def f(x):
    d = Counter(x)
    return ((d.get(0, 0), d.get(1, 0), d.get(2, 0), d.get(3, 0)))

The output:

I want to remove any zero value from (counts) column, so the expercted ouptput is:

Ihave tried this code to remove zero values but it not working!

def trim_zeros_in_rows(ndarr):
    return np.array([np.trim_zeros(row) for row in ndarr])

print(trim_zeros_in_rows(df['counts']))

CodePudding user response：

Using a list comprehension seems to do the trick (if you don't care about the type, you get rid of the tuple() call):

df['count'].apply(lambda x: tuple([y for y in x if y != 0]))

Giving you:

0    (5, 2, 2)
1    (1, 6, 2)
2       (7, 2)
3       (3, 6)
4       (7, 2)
Name: count, dtype: object