How do I Pass a List of Series to a Pandas DataFrame?

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 simpl

Answer 1

Build the list of series:

import pandas as pd
import numpy as np

> series = [pd.Series(np.random.rand(3), name=c) for c in list('abcdefg')]

First method pd.DataFrame.from_items:

> pd.DataFrame.from_items([(s.name, s) for s in series])
          a         b         c         d         e         f         g
0  0.071094  0.077545  0.299540  0.377555  0.751840  0.879995  0.933399
1  0.538251  0.066780  0.415607  0.796059  0.718893  0.679950  0.502138
2  0.096001  0.680868  0.883778  0.210488  0.642578  0.023881  0.250317

Second method pd.concat:

> pd.concat(series, axis=1)
          a         b         c         d         e         f         g
0  0.071094  0.077545  0.299540  0.377555  0.751840  0.879995  0.933399
1  0.538251  0.066780  0.415607  0.796059  0.718893  0.679950  0.502138
2  0.096001  0.680868  0.883778  0.210488  0.642578  0.023881  0.250317

Answer 2

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

Answer 3

a = pd.Series(data=[1,2,3])
b = pd.Series(data=[4,5,6])
a.name = 'a'
b.name= 'b'

pd.DataFrame(zip(a,b), columns=[a.name, b.name])

or just concat dataframes

pd.concat([pd.DataFrame(a),pd.DataFrame(b)], axis=1)

In [53]: %timeit pd.DataFrame(zip(a,b), columns=[a.name, b.name])
1000 loops, best of 3: 362 us per loop

In [54]: %timeit pd.concat([pd.DataFrame(a),pd.DataFrame(b)], axis=1)
1000 loops, best of 3: 808 us per loop

Answer 4

Simply passing the list of Series to DataFrame then transposing seems to work too. It will also fill in any indices that are missing from one or the other Series.

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.DataFrame(data).T
print(df)

Answer 5

Check out DataFrame.from_items too

Answer 6

You can first create an empty DataFrame and then use append() to it.

df = pd.DataFrame()

then:

df = df.append(list_series)

I also like to make sure the previous script that created list_series won't mess my dataframe up:

df.drop_duplicates(inplace=True)