I have my pandas dataframe and i need to find the index of a certain value. But the thing is, this df does from an other one where i had to cut some part using the df.loc, so it ends up like :
index value
1448 31776
1449 32088
1450 32400
1451 32712
1452 33024
Let's say i need to find the index of the value '32400', with the function df.index[df.value == 32400] i get 1450, but what I want is 2.
Would you know how i could get this value?
First idea is create default index starting by 0 by DataFrame.reset_index with drop=True:
df = df.reset_index(drop=True)
idx = df.index[df.value == 32400]
print (idx)
Int64Index([2], dtype='int64')
Or use numpy - e.g. by numpy.where with condition for positions of match:
idx = np.where(df.value == 32400)[0]
print (idx)
[2]
Or use numpy.argmax - it working well if match at least one value:
idx = np.argmax(df.value == 32400)
print (idx)
2
idx = np.argmax(df.value == 10)
print (idx)
0