don't know how to coerce int64 and float64

Question

I have a list which is filled form excel file (import to pandas)

a=[df.math[0],df.bio[0],df.chemistry[0]]

when I pass mean(a) it gives me the following error:

don't know how to coerce int64 and float64

How to fix it? I tried a=[float(df.math[0]),float(df.bio[0]),float(df.chemistry[0])] - but still does not work

What do you think is the problem ?

Answer 1

I think here the simpliest is use numpy.mean :

x = np.mean(a)

Sample :

 df = pd.DataFrame({
        'A':list('abcdef'),
         'math':[4,5,4,5,5,4],
         'chemistry':[7.3434,8,9,4,2,3],
         'bio':[1,3,5,7,1,0],
         'E':[5,3,6,9,2,4],
         'F':list('aaabbb')
})

x = np.mean(a)
print (x) 
4.114466666666666

Pandas solution:

x = df.loc[0, ['math','bio','chemistry']].mean()
print (x) 
4.114466666666666

Also for me working converting all values to floats:

import statistics 

a = [float(df.math[0]),float(df.bio[0]),float(df.chemistry[0])]
x = statistics.mean(a)
print (x) 
4.114466666666667

---

import statistics 

a = [float(x) for x in a]
x = statistics.mean(a)
print (x) 
4.114466666666667