Rolling
=======

.. currentmodule:: pandasCore

Rolling window operations for calculating statistics over a sliding window.

Example
-------

.. code-block:: python

   import pandasCore as pd

   s = pd.Series([1, 2, 3, 4, 5])
   s.rolling(window=3).mean()  # [NaN, NaN, 2.0, 3.0, 4.0]
   s.rolling(window=3).sum()   # [NaN, NaN, 6.0, 9.0, 12.0]

Parameters
----------

.. list-table::
   :widths: 15 10 10 65
   :header-rows: 1

   * - Parameter
     - Type
     - Default
     - Description
   * - window
     - int
     - required
     - Size of moving window
   * - min_periods
     - int
     - None
     - Minimum observations needed
   * - center
     - bool
     - False
     - Set labels at center
   * - win_type
     - str
     - None
     - Window type for weighted
   * - on
     - str
     - None
     - Column to use for window
   * - axis
     - int
     - 0
     - Axis to roll on
   * - closed
     - str
     - None
     - Which side is closed

Methods
-------

.. list-table::
   :widths: 20 80
   :header-rows: 1

   * - Method
     - Description
   * - count()
     - Count of observations
   * - sum()
     - Sum of values
   * - mean()
     - Mean of values
   * - median()
     - Median of values
   * - var()
     - Variance
   * - std()
     - Standard deviation
   * - min()
     - Minimum
   * - max()
     - Maximum
   * - corr()
     - Correlation
   * - cov()
     - Covariance
   * - skew()
     - Skewness
   * - kurt()
     - Kurtosis
   * - apply(func)
     - Apply custom function
   * - agg(func)
     - Aggregate with function(s)
   * - quantile(q)
     - Quantile
   * - sem()
     - Standard error of mean
   * - rank()
     - Rank