CODEWITHSUNDEEP
pythonpandasdataframe
ben121
ben121

Reputation: 897

Pandas - conditional row average

I have a dataframe:

x = pd.DataFrame({'1':[1,2,3,2,5,6,7,8,9], '2':[2,5,6,8,10,np.nan,6,np.nan,np.nan], 
    '3':[10,10,10,np.nan,np.nan,np.nan,np.nan,np.nan,np.nan]})

I am trying to generate an average of a row but only on values greater than 5. For instance - if a row had values of 3, 6, 10. The average would be 8 ((6+10)/2). The 3 would be ignored as it is below 5.

The equivalent in excel would be =AVERAGEIF(B2:DX2,">=5")

Upvotes: 1

Views: 174

Answers (2)

Ric S
Ric S

Reputation: 9277

You can create a small custom function which, inside each row, filters out values smaller or equal than a certain value and apply it to each row of your dataframe

def average_if(s, value=5):
    s = s.loc[s > value]
    return s.mean()

x.apply(average_if, axis=1)

0    10.0
1    10.0
2     8.0
3     8.0
4    10.0
5     6.0
6     6.5
7     8.0
8     9.0
dtype: float64

Upvotes: 2

anky
anky

Reputation: 75130

You can mask the values greater than 5 then take mean:

x.where(x>5).mean(1)

Or:

x.mask(x<=5).mean(1)

Upvotes: 3

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