Merge multiple column values into one column in python pandas

Question

I have a pandas data frame like this:

   Column1  Column2  Column3  Column4  Column5
 0    a        1        2        3        4
 1    a        3        4            


        

Answer 1

If you have lot of columns say - 1000 columns in dataframe and you want to merge few columns based on particular column name e.g. -Column2 in question and arbitrary no. of columns after that column (e.g. here 3 columns after 'Column2 inclusive of Column2 as OP asked).

We can get position of column using .get_loc() - as answered here

source_col_loc = df.columns.get_loc('Column2') # column position starts from 0

df['ColumnA'] = df.iloc[:,source_col_loc+1:source_col_loc+4].apply(
    lambda x: ",".join(x.astype(str)), axis=1)

df

Column1  Column2  Column3  Column4  Column5  ColumnA
0       a        1        2        3        4  1,2,3,4
1       a        3        4        5      NaN    3,4,5
2       b        6        7        8      NaN    6,7,8
3       c        7        7      NaN      NaN      7,7

To remove NaN, use .dropna() or .fillna()

Hope it helps!