api documentation¶
base module¶
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Base tranformer class which all other transformers in the package inherit from. |
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Tranformer that applies a pandas.DataFrame method. |
capping module¶
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Transformer to cap numeric values at both or either minimum and maximum values. |
Transformer to set values outside of a range to null. |
comparison module¶
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Transformer to check if two columns are equal. |
dates module¶
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Transformer to generate a boolean column indicating if one date is between two others. |
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Class to transform calculate the difference between 2 date fields in specified units. |
Transformer to calculate the number of years between two dates. |
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Tranformer that applies a pandas.Series.dt method. |
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Class to transform convert specified column to datetime. |
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Transformer to extract various features from datetime var. |
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Transformer to derive a feature in a dataframe by calculating the sine or cosine of a datetime column in a given unit (e.g hour), with the option to scale period of the sine or cosine to match the natural period of the unit (e.g. |
imputers module¶
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Transformer to impute null values with an arbitrary pre-defined value. |
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Base imputer class containing standard transform method that will use pd.Series.fillna with the values in the impute_values_ attribute. |
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Transformer to impute missing values with the mean of the supplied columns. |
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Transformer to impute missing values with the median of the supplied columns. |
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Transformer to impute missing values with the mode of the supplied columns. |
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Class to impute missing values with; the value for which the average response is closest to the average response for the unknown levels. |
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Class to create a binary indicator column for null values. |
mapping module¶
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Base Transformer Extension for mapping transformers. |
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Mixin class to apply standard pd.Series.map transform method. |
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Transformer to map values in columns to other values e.g. |
Transformer to adjust values in one column based on the values of another column. |
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Transformer to apply a multiplicative adjustment to values in one column based on the values of another column. |
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Transformer to apply an additive adjustment to values in one column based on the values of another column. |
misc module¶
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Transformer to set value of column(s) to a given value. |
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Transformer to set transform columns in a dataframe to a dtype. |
nominal module¶
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Base Transformer extension for nominal transformers. |
Transformer to group together rare levels of nominal variables into a new level, labelled ‘rare’ (by default). |
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Transformer to apply mean response encoding. |
Transformer to convert columns containing nominal values into integer values. |
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Transformer to encode categorical variables into ascending rank-ordered integer values variables by mapping it’s levels to the target-mean response for that level. |
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Transformer to convert cetegorical variables into dummy columns. |
numeric module¶
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Transformer to apply log transformation. |
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Class to bin a column into discrete intervals. |
This transformer applies a pandas.DataFrame method to two columns (add, sub, mul, div, mod, pow). |
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Transformer to perform scaling of numeric columns. |
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Transformer that generates interaction features. |
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Transformer that generates variables using Principal component analysis (PCA). |
strings module¶
Tranformer that applies a pandas.Series.str method. |
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Transformer to combine data from specified columns, of mixed datatypes, into a new column containing one string. |