Creating an empty Pandas DataFrame, then filling it?

Here’s a couple of suggestions:

Use date_range for the index:

import datetime
import pandas as pd
import numpy as np

todays_date = datetime.datetime.now().date()
index = pd.date_range(todays_date-datetime.timedelta(10), periods=10, freq='D')

columns = ['A','B', 'C']

Note: we could create an empty DataFrame (with NaNs) simply by writing:

df_ = pd.DataFrame(index=index, columns=columns)
df_ = df_.fillna(0) # with 0s rather than NaNs

To do these type of calculations for the data, use a numpy array:

data = np.array([np.arange(10)]*3).T

Hence we can create the DataFrame:

In [10]: df = pd.DataFrame(data, index=index, columns=columns)

In [11]: df
Out[11]: 
            A  B  C
2012-11-29  0  0  0
2012-11-30  1  1  1
2012-12-01  2  2  2
2012-12-02  3  3  3
2012-12-03  4  4  4
2012-12-04  5  5  5
2012-12-05  6  6  6
2012-12-06  7  7  7
2012-12-07  8  8  8
2012-12-08  9  9  9