Encoding
| Method | Definition |
|---|---|
| vDataFrame[].decode | Encodes the vcolumn using a user-defined encoding. |
| vDataFrame[].discretize | Discretizes the vcolumn using the input method. |
| vDataFrame.get_dummies | Encodes the vcolumns using the One-Hot Encoding algorithm. |
| vDataFrame[].get_dummies | Encodes the vcolumn using the One-Hot Encoding algorithm. |
| vDataFrame[].label_encode | Encodes the vcolumn using a bijection from the different categories to [0, n - 1] |
| vDataFrame[].mean_encode | Encode the vcolumn using the average of the response partitioned by the different vcolumn categories. |
Dealing with Missing Values
| Method | Definition |
|---|---|
| vDataFrame.dropna | Filters the vDataFrame where the input vcolumns are missing. |
| vDataFrame[].dropna | Filters the vDataFrame where the vcolumn is missing. |
| vDataFrame.fillna | Fills the vcolumns missing elements using specific rules. |
| vDataFrame[].fillna | Fills the vcolumn missing elements using specific rules. |
Normalization and Global Outliers
| Method | Definition |
|---|---|
| vDataFrame[].clip | Clips the vcolumn. |
| vDataFrame[].fill_outliers | Fills the vcolumns outliers using the input method. |
| vDataFrame.normalize | Normalizes the input vcolumns using the input method. |
| vDataFrame[].normalize | Normalizes the input vcolumns using the input method. |
| vDataFrame.outliers | Adds a new vcolumn labeled with 0 and 1. 1 means that the record is a global outlier. |
Splitting into Train/Test
| Method | Definition |
|---|---|
| vDataFrame.train_test_split | Creates 2 vDataFrame (train/test) which can be to use to evaluate a model. |
Data Types Conversion
| Method | Definition |
|---|---|
| vDataFrame.astype | Converts the vcolumns to the input types. |
| vDataFrame[].astype | Converts the vcolumn to the input type. |
| vDataFrame.bool_to_int | Converts all the booleans vcolumns to integers. |
Renaming
| Method | Definition |
|---|---|
| vDataFrame[].rename | Renames the vcolumn. |