statsmodels.tsa.tsatools.add_lag¶
-
statsmodels.tsa.tsatools.add_lag(x, col=
None
, lags=1
, drop=False
, insert=True
)[source]¶ Returns an array with lags included given an array.
- Parameters:¶
- xarray_like
An array or NumPy ndarray subclass. Can be either a 1d or 2d array with observations in columns.
- col
int
orNone
col can be an int of the zero-based column index. If it’s a 1d array col can be None.
- lags
int
The number of lags desired.
- dropbool
Whether to keep the contemporaneous variable for the data.
- insertbool or
int
If True, inserts the lagged values after col. If False, appends the data. If int inserts the lags at int.
- Returns:¶
- array
ndarray
Array with lags
- array
Notes
Trims the array both forward and backward, so that the array returned so that the length of the returned array is len(X) - lags. The lags are returned in increasing order, ie., t-1,t-2,…,t-lags
Examples
>>> import statsmodels.api as sm >>> data = sm.datasets.macrodata.load() >>> data = data.data[['year','quarter','realgdp','cpi']] >>> data = sm.tsa.add_lag(data, 'realgdp', lags=2)
Last update:
Dec 16, 2024