How To Rename Columns Dynamically Before Unstack In Pandas?

I have the below dataframe created using groupby and sum :- year_month Country 2008-01 Afghanistan 2 Albania 3 A

Solution 1:

I think need Series.unstack with DataFrame.add_prefix:

df = s.unstack().add_prefix('der_value_')
print (df)
Country     der_value_Afghanistan  der_value_Albania  der_value_Argentina
year_month                                                               
2008-01                         2                  3                    4
2008-02                         3                  4                    5

For index to column add DataFrame.rename_axis with DataFrame.reset_index:

df = s.unstack().add_prefix('der_value_').rename_axis(None, axis=1).reset_index()
print (df)
  year_month  der_value_Afghanistan  der_value_Albania  der_value_Argentina
0    2008-01                      2                  3                    4
1    2008-02                      3                  4                    5

---

Modify MultiInex before unstack is also possible by MultiIndex.from_arrays:

a=s.index.get_level_values(0)b='der_value_'+s.index.get_level_values(1)s.index=pd.MultiIndex.from_arrays([a,b],names=s.index.names)print(s)year_monthCountry2008-01     der_value_Afghanistan2der_value_Albania3der_value_Argentina42008-02     der_value_Afghanistan3der_value_Albania4der_value_Argentina5Name:a,dtype:int64df=s.unstack()print(df)Countryder_value_Afghanistander_value_Albaniader_value_Argentinayear_month2008-01                         2342008-02                         345

Solution 2:

Creative use of the MultiIndex internals

idx, cols = s.index.levels
i, j = s.index.labels

v = np.zeros((len(idx), len(cols)), dtype=s.dtype)
v[i, j] = s


pd.DataFrame(
    np.column_stack([idx, v]),
    columns=np.append('year_month', 'der_value_' + cols)
)

  year_month der_value_Afghanistan der_value_Albania der_value_Argentina
02008-0123412008-02345