How can I convert columns to rows in Pandas?

Question

I have something like this:

Values     Time
  22        0
  45        1
  65        2
  78        0
  12        1
  45        2

and I want this

Answer 1

This is pivot creating the index with cumcount

df['idx'] = 'Val' + (df.groupby('Time').cumcount()+1).astype(str)
df.pivot(index='idx', columns='Time', values='Values').rename_axis(None)

Output:

Time   0   1   2
Val1  22  45  65
Val2  78  12  45

Answer 2

If your time-delta is constant, ordered and has no missing values:

DELTA = 3
new_values = [df['Values'].iloc[i*DELTA:i*DELTA+DELTA].values.transpose() for i in range(int(len(df)/DELTA))]
df_new = pd.DataFrame(new_values , index=['Val'+str(i+1) for i in range(len(new_values ))])

print(df_new)
         0   1   2
Val1    22  45  65
Val2    78  12  45

Not a pretty solution, but maybe it helps. :-)

Answer 3

You need to transpose your array/matrix.

Use

list(map(list, zip(*l)))

where list is your list