I extracted three columns from a larger data frame (recent_grads) as follows...
df = recent_grads.groupby('Major_category')['Men', 'Women'].sum()
However, when I print df, it comes up as follows...
Men Women
Major_category
Agriculture & Natural Resources 40357.0 35263.0
Arts 134390.0 222740.0
Biology & Life Science 184919.0 268943.0
Business 667852.0 634524.0
Communications & Journalism 131921.0 260680.0
Computers & Mathematics 208725.0 90283.0
Education 103526.0 455603.0
Engineering 408307.0 129276.0
Health 75517.0 387713.0
Humanities & Liberal Arts 272846.0 440622.0
Industrial Arts & Consumer Services 103781.0 126011.0
Interdisciplinary 2817.0 9479.0
Law & Public Policy 91129.0 87978.0
Physical Sciences 95390.0 90089.0
Psychology & Social Work 98115.0 382892.0
Social Science 256834.0 273132.0
How do I get Major_category heading in the same row as Men and Women headings? I tried to put the three columns in a new data frame as follows...
df1 = df[['Major_category', 'Men', 'Women']].copy()
This gives me an error (Major_category not in index)
Hi man you should try reset_index https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.reset_index.html:
df = df.groupby('Major_category')['Men', 'Women'].sum()
# Print the output.
md = df.reset_index()
print(md)