I am having large data set (82 variables) Is there any way to arrange data such a way that I have to get all numerical variables firstly then categorical variables so that I can run hypothesis testing or exploratory data analysis(eda) by having loop.

If not is there any way to do eda in simpler manner because I can't check the correlation or chi.square test for each variable


Let your data frame be df. First get the numeric columns:

num_col = df.select_dtypes('number').columns

Then get the remaining columns.

non_num_col = set(df.columns) - set(df.select_dtypes('number').columns)

Merge as required.

df = pd.concat([df[num_col], df[list(non_num_col)]], axis=1)

The columns are now in the desired sequence.

| improve this answer | |
  • $\begingroup$ Thanks for the answer $\endgroup$ – user12490809 Dec 26 '19 at 7:01
  • $\begingroup$ If it worked. Please upvote and Mark as resolved. $\endgroup$ – Ansh Dec 26 '19 at 11:48
  • $\begingroup$ Next time please format your answer properly. $\endgroup$ – Peter Jan 1 at 22:59

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