Question

I realize Dataframe takes a map of {‘series_name’:Series(data, index)}. However, it automatically sorts that map even if the map is an OrderedDict().

Is there a simple way to pass a list of Series(data, index, name=name) such that the order is preserved and the column names are the series.name? Is there an easy way if all the indices are the same for all the series?

I normally do this by just passing a numpy column_stack of series.values and specifying the column names. However, this is ugly and in this particular case the data is strings not floats.

Answer 1

You could use pandas.concat:

import pandas as pd
from pandas.util.testing import rands

data = [pd.Series([rands(4) for j in range(6)],
                  index=pd.date_range('1/1/2000', periods=6),
                  name='col'+str(i)) for i in range(4)]

df = pd.concat(data, axis=1, keys=[s.name for s in data])
print(df)

yields

            col0  col1  col2  col3
2000-01-01  GqcN  Lwlj  Km7b  XfaA
2000-01-02  lhNC  nlSm  jCYu  XLVb
2000-01-03  sSRz  PFby  C1o5  0BJe
2000-01-04  khZb  Ny9p  crUY  LNmc
2000-01-05  hmLp  4rVp  xF2P  OmD9
2000-01-06  giah  psQb  T5RJ  oLSh