CODEWITHSUNDEEP
pandas
Talya Shacham
Talya Shacham

Reputation: 37

Sort specific values from a column in panda data frame

i have a data frame, for example :

df =     ID  aa_len                                             aa_seq  \
0  001      45  [M, R, S, R, Y, P, L, L, R, G, E, A, V, A, V, ...   
1  002      45  [M, R, S, R, Y, P, L, L, R, G, E, A, V, A, V, ...   

   mut_position  
0              [-1]  
1  [5, 94, 95, 132]

The "mut_position" can be -1 or other non negative number (2,3,4) or a list of few numbers. for example it can be -1 as in 001. a list of a few like in 002 or one number- for example 4. i need to count the number of subjects who doesnt have -1.

i tried to so that by comparing to -1 and collect the ones that r different but it dosent seems to work...

def count_mutations(df, ref_aa_len):
nomis = -1
mutation = (df['mut_position']) != nomis 
print (mutation)

what i get it True for both (ignore the ref_aa_len, that should come later)-

0    True
1    True

Upvotes: 1

Views: 32

Answers (1)

jezrael
jezrael

Reputation: 863166

I think need list compehension with generator and sum of boolean Trues:

df['non_negative'] = [sum(y != -1 for y in x) for x in df['mut_position']]
print (df)
       mut_position  non_negative
0              [-1]             0
1  [5, 94, 95, 132]             4

If possible scalars also:

print (df)
    mut_position
0           [-1]
1  [5,94,95,132]
2              6
3             -1

df['non_negative'] = [sum(y != -1 for y in x)  
                     if isinstance(x, list) 
                     else int(x != -1) for x in df['mut_position']]
print (df)
       mut_position  non_negative
0              [-1]             0
1  [5, 94, 95, 132]             4
2                 6             1
3                -1             0

If need check first values if list for -1 and filter by boolean indexing:

df = pd.DataFrame({'mut_position':[[-1], [5,94,95,132],[2,-1], [-1]]})

print (df)
       mut_position
0              [-1]
1  [5, 94, 95, 132]
2           [2, -1]
3              [-1]

df1 = df[df['mut_position'].str[0] != -1 ]
print (df1)
       mut_position
1  [5, 94, 95, 132]
2           [2, -1]

Detail:

str[0] working for select first char of string or first value of iterable:

 print (df['mut_position'].str[0])
0   -1
1    5
2    2
3   -1
Name: mut_position, dtype: int64

And for check -1 for any position use all:

df1 = df[[all(y != -1 for y in x) for x in df['mut_position']]]
print (df1)
       mut_position
1  [5, 94, 95, 132]

List comprehension return boolena list:

print ([all(y != -1 for y in x) for x in df['mut_position']])
[False, True, False, False]

Upvotes: 1

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