Several important functionalities

Here, we introduce several important functionalities that we are going to use in the rest of the chapters. The Series() function included in the Pandas module would help us to generate time series. When dealing with time series, the most important variable is date. This is why we explain the date variable in more detail. Data.Frame is used intensively in Python and other languages, such as R.

Using pd.Series() to generate one-dimensional time series

We could easily use the pd.Series() function to generate our time series; refer to the following example:

>>>import pandas as pd
>>>x = pd.date_range('1/1/2013', periods=252)
>>>data = pd.Series(randn(len(x)), index=x)
>>>data.head()
2013-01-01    0.776670
2013-01-02    0.128904
2013-01-03   -0.064601
2013-01-04    0.988347
2013-01-05    0.459587
Freq: D, dtype: float64
>>>data.tail()
2013-09-05   -0.167599
2013-09-06    0.530864
2013-09-07    1.378951
2013...