To select multiple columns, extract and view them thereafter: df is previously named data frame, than create new data frame df1, and select the columns A to D which you want to extract and view.

df1 = pd.DataFrame(data_frame, columns=['Column A', 'Column B', 'Column C', 'Column D'])
df1

All required columns will show up!

To select multiple columns, extract and view them thereafter: df is the previously named data frame. Then create a new data frame df1, and select the columns A to D which you want to extract and view.

df1 = pd.DataFrame(data_frame, columns=['Column A', 'Column B', 'Column C', 'Column D'])
df1

All required columns will show up!

To select multiple columns, extract and view them thereafter! df is previously named data frame, than create new data frame df1, and select the columns A to D which you want to extract and view!

df1=pd.DataFrame(data_frame, columns=['Column A', 'Column B', 'Column C', 'Column D'])

df1

All required columns will show up!

To select multiple columns, extract and view them thereafter: df is previously named data frame, than create new data frame df1, and select the columns A to D which you want to extract and view.

df1 = pd.DataFrame(data_frame, columns=['Column A', 'Column B', 'Column C', 'Column D'])
df1

All required columns will show up!