Note
This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the What you really need to know section for the big picture.
julearn.prepare.prepare_input_data#
- julearn.prepare.prepare_input_data(X, y, df, pos_labels, groups, X_types)#
Prepare the input data and variables for the pipeline.
- Parameters:
- Xstr, list(str)
The features to use. See https://juaml.github.io/julearn/input.html for details.
- ystr
The targets to predict. See https://juaml.github.io/julearn/input.html for details.
- dfpandas.DataFrame with the data.
See https://juaml.github.io/julearn/input.html for details.
- pos_labelsstr, int, float or list | None
The labels to interpret as positive. If not None, every element from y will be converted to 1 if is equal or in pos_labels and to 0 if not.
- groupsstr | None
The grouping labels in case a Group CV is used. See https://juaml.github.io/julearn/input.html for details.
- X_typesdict | None
A dictionary containing keys with column type as a str and the columns of this column type as a list of str.
- Returns
- ——-
- df_Xpandas.DataFrame
A dataframe with the features for each sample.
- df_ypandas.Series
A series with the y variable (target) for each sample.
- df_groupspandas.Series
A series with the grouping variable for each sample (if specified in the groups parameter).
- Raises:
- ValueError
If there is any error on the input data and parameters validation.
- Warns:
- RuntimeWarning
If the input data and parameters might have inconsistencies.