Calculte kurtosis and skewness using for loop

Question

i'm trying to calculteskewness and kurtosis for different fields. I want to get in the end table with each field name. the kurtosis and the skewness. for that I have written the next code:

for i in data_dis.columns:
    print('skewness',i,':',i.skew())
    print('Kurtosis',i,':',i.kurtosis())

AttributeError: 'str' object has no attribute 'skew'

I am 100% sure that there is no string in my database as you can see from the info:

data_dis.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 1412 entries, 0 to 1411
Data columns (total 13 columns):
HR90     1412 non-null float64
HC90     1412 non-null float64
PO90     1412 non-null int64
RD90     1412 non-null float64
PS90     1412 non-null float64
UE90     1412 non-null float64
DV90     1412 non-null float64
MA90     1412 non-null float64
POL90    1412 non-null float64
DNL90    1412 non-null float64
BLK90    1412 non-null float64
GI89     1412 non-null float64
FH90     1412 non-null float64

I saw that skew works here: http://www.christianherta.de/lehre/dataScience/exploratory/intro-explorative-data-analysis.php

My end goal is to create a table with the skewness and kurtosis data for each field.

Answer 1

You don't need a for loop, you can just calculate skewness and kurtosis for each numerical column using the dataframe methods:

data_dis.skew()
data_dis.kurtosis()

They both return a Pandas Series, with indexes column names and as values the column skewness and column kurtosis respectively.

Answer 2

data_dis.columns provide the column names, not the values