Rolling Window In Pandas - Explanation

Question

I am trying to learn Pandas library for Python, and then I came across the concept of "Rolling Window" for time-series analysis. I have never been a good student of Statistics, so I am a bit lost.

Please explain the concept, preferably using a simple example, and maybe a code snippet.

Answer 1

Demo:

Setup:

In [11]: df = pd.DataFrame({'a':np.arange(10, 17)})

In [12]: df
Out[12]:
    a
0  10
1  11
2  12
3  13
4  14
5  15
6  16

Rolling sum for the 2 rows window:

In [13]: df['a'].rolling(2).sum()
Out[13]:
0     NaN  # sum of the current and previous value: 10 + NaN = NaN
1    21.0  # sum of the current and previous value: 10 + 11
2    23.0  # sum of the current and previous value: 11 + 12
3    25.0  # ...
4    27.0
5    29.0
6    31.0
Name: a, dtype: float64

Rolling sum for the 3 rows window:

In [14]: df['a'].rolling(3).sum()
Out[14]:
0     NaN  # sum of current value and two preceeding rows: 10 + NaN + Nan
1     NaN  # sum of current value and two preceeding rows: 10 + 11 + Nan
2    33.0  # sum of current value and two preceeding rows: 10 + 11 + 12
3    36.0  # ...
4    39.0
5    42.0
6    45.0
Name: a, dtype: float64