vDataFrame.regr¶
In [ ]:
vDataFrame.regr(columns: list = [],
method: str = "r2",
show: bool = True,
ax=None,
**style_kwds,)
Computes the Regression Matrix of the vDataFrame.
Parameters¶
Name | Type | Optional | Description |
---|---|---|---|
columns | list | ✓ | List of the vcolumns names. If empty, all the numerical vcolumns will be used. |
method | str | ✓ | Method to use to compute the regression matrix.
|
show | bool | ✓ | If set to True, the Regression Matrix will be drawn using Matplotlib.. |
ax | Matplotlib axes object | ✓ | The axes to plot on. |
**style_kwds | any | ✓ | Any optional parameter to pass to the Matplotlib functions. |
Returns¶
tablesample : An object containing the result. For more information, see utilities.tablesample.
Example¶
In [5]:
from verticapy.datasets import load_titanic
titanic = load_titanic()
display(titanic)
In [6]:
# Slope
titanic.regr(method = "beta")
In [3]:
# Intercept
titanic.regr(method = "alpha")
See Also¶
vDataFrame.acf | Computes the Correlations between a vcolumn and its lags. |
vDataFrame.corr | Computes the Correlation Matrix of the vDataFrame. |
vDataFrame.cov | Computes the Covariance Matrix of the vDataFrame. |