Get the most repeated value from columns of list other than zero in pandas data frame

Question

I have a following data frame,

df1=
mac           gw_mac        ibeaconMajor  ibeaconMinor     
ac233f264920  ac233fc015f6  [1, 0, 1]        [1, 0] 
ac233f26492b  ac233fc015f6  [0, 0, 0]        [0, 0] 
ac233f264933  ac233fc015f6  [0, 1, 1]        [0, 2]

If all the values in a list(from the columns "ibeaconMajor" & "ibeaconMinor") is "0" it should return as "0" or else it should return frequently occurred non-zero values from a list as like below,

df1=
mac           gw_mac        ibeaconMajor  ibeaconMinor     
ac233f264920  ac233fc015f6  1             1 
ac233f26492b  ac233fc015f6  0             0 
ac233f264933  ac233fc015f6  1             2

jezrael · Accepted Answer · 2019-08-16 08:34:02Z

1

Idea is use DataFrame.applymap for elementwise apply lambda function - first remve 0 values in list comprehension, get top values by Counter and add next with iter for possible add 0 if all 0 values - here in tuple for possible select first value of tuples:

from collections import Counter

cols = ['ibeaconMajor','ibeaconMinor']

f = lambda x: next(iter(Counter([y for y in x if y != 0]).most_common(1)), (0,))[0]
#alternative
#f = lambda x: next(iter(Counter(filter(lambda y: y != 0, x)).most_common(1)), (0,))[0]
df[cols] = df[cols].applymap(f)

print (df)
            mac        gw_mac  ibeaconMajor  ibeaconMinor
0  ac233f264920  ac233fc015f6             1             1
1  ac233f26492b  ac233fc015f6             0             0
2  ac233f264933  ac233fc015f6             1             2

edited Aug 16, 2019 at 8:34

answered Aug 16, 2019 at 7:58

jezrael

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