Pandas - unstack column values into new columns

Question

I have a large dataframe and I am storing a lot of redundant values that are making it hard to handle my data. I have a dataframe of the form:

import pandas          


        

Answer 1

You can use pivot_table with reset_index and rename_axis (new in pandas 0.18.0):

print (df.pivot_table(index=['meta1','meta2'], 
                      columns='name', 
                      values='data', 
                      aggfunc='first')
         .reset_index()
         .rename_axis(None, axis=1))

  meta1 meta2  n1  n2
0     a     g  y1  y2
1     b     h  y3  y4

But better is use aggfunc join:

print (df.pivot_table(index=['meta1','meta2'], 
                      columns='name', 
                      values='data', 
                      aggfunc=', '.join)
         .reset_index()
         .rename_axis(None, axis=1))

  meta1 meta2  n1  n2
0     a     g  y1  y2
1     b     h  y3  y4

Explanation, why join is generally better as first:

If use first, you can lost all data which are not first in each group by index, but join concanecate them:

import pandas as pd

df = pd.DataFrame([["a","g","n1","y1"], 
                   ["a","g","n2","y2"], 
                   ["a","g","n1","y3"], 
                   ["b","h","n2","y4"]], columns=["meta1", "meta2", "name", "data"])

print (df)
  meta1 meta2 name data
0     a     g   n1   y1
1     a     g   n2   y2
2     a     g   n1   y3
3     b     h   n2   y4

print (df.pivot_table(index=['meta1','meta2'], 
                      columns='name', 
                      values='data', 
                      aggfunc='first')
         .reset_index()
         .rename_axis(None, axis=1))
  meta1 meta2    n1  n2
0     a     g    y1  y2
1     b     h  None  y4

print (df.pivot_table(index=['meta1','meta2'], 
                      columns='name', 
                      values='data', 
                      aggfunc=', '.join)
         .reset_index()
         .rename_axis(None, axis=1))

  meta1 meta2      n1  n2
0     a     g  y1, y3  y2
1     b     h    None  y4