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

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

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

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