mars.dataframe.Series.autocorr¶

Series.autocorr(lag=1)¶

Compute the lag-N autocorrelation.

This method computes the Pearson correlation between the Series and its shifted self.

Parameters: lag (int, default 1) – Number of lags to apply before performing autocorrelation.
Returns: The Pearson correlation between self and self.shift(lag).
Return type: float

See also

Series.corr: Compute the correlation between two Series.
Series.shift: Shift index by desired number of periods.
DataFrame.corr: Compute pairwise correlation of columns.
DataFrame.corrwith: Compute pairwise correlation between rows or columns of two DataFrame objects.

Notes

If the Pearson correlation is not well defined return ‘NaN’.

Examples

>>> import mars.dataframe as md
>>> s = md.Series([0.25, 0.5, 0.2, -0.05])
>>> s.autocorr().execute()  
0.10355...
>>> s.autocorr(lag=2).execute()  
-0.99999...

If the Pearson correlation is not well defined, then ‘NaN’ is returned.

>>> s = md.Series([1, 0, 0, 0])
>>> s.autocorr().execute()
nan

mars.dataframe.Series.any mars.dataframe.Series.corr