pandas - multiple columns to “column name - value” columns

Question

I have a pandas dataframe with multiple columns and I want to "flatten" it to just two columns - one with column name and the other with values. Eg

df1 = pd.DataFrame({'A':[1,2],'B':[2,3], 'C':[3,4]})

How can I convert it to look like:

df2 = pd.DataFrame({'column name': ['A','A','B','B','C','C'], 'value': [1,2,2,3,3,4]})

Answer 1

You can stack to stack all column values into a single, column, then drop the first level index calling reset_index , overwrite the column names with the ones you desire and then finally sort using sort_values :

In [37]:
df2 = df1.stack().reset_index(level=0, drop=True).reset_index()
df2.columns = ['column name', 'value']
df2.sort_values(['column name', 'value'], inplace=True)
df2

Out[37]:
  column name  value
0           A      1
3           A      2
1           B      2
4           B      3
2           C      3
5           C      4

Answer 2

You can reshape by stack to MultiIndex Series and then reset_index with sort_values :

df2 = df1.stack().reset_index(level=0, drop=True).reset_index().sort_values('index')
df2.columns = ['column name','value']
print (df2)
  column name  value
0           A      1
3           A      2
1           B      2
4           B      3
2           C      3
5           C      4

One row solution with rename column index to column name :

df2 = df1.stack()
         .reset_index(level=0, drop=True)
         .reset_index(name='value')
         .sort_values(['index'])
         .rename(columns={'index':'column name'})
print (df2)
  column name  value
0           A      1
3           A      2
1           B      2
4           B      3
2           C      3
5           C      4

If need sort by both columns:

df2 = df1.stack().reset_index(level=0, drop=True).reset_index().sort_values(['index',0])
df2.columns = ['column name','value']
print (df2)
  column name  value
0           A      1
3           A      2
1           B      2
4           B      3
2           C      3
5           C      4