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
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