helikite.processing.post.tools

Functions

choose_outliers(df, y[, outlier_file])

Creates a plot to interactively select outliers in the data.

choose_flags(df, y[, flag_file, key, value])

Creates a plot to interactively select and assign flags to data points.

Module Contents

helikite.processing.post.tools.choose_outliers(df, y, outlier_file='outliers.csv')

Creates a plot to interactively select outliers in the data.

A plot is generated where two variables are plotted, and the user can click on points to select or deselect them as outliers, or use Plotly’s selection tools to select multiple points at once.

Parameters:

  • df (pandas.DataFrame) – The dataframe containing the data

  • y (str) – The column name of the y-axis variable

  • outlier_file (str) – The path to the CSV file to store the outliers

helikite.processing.post.tools.choose_flags(df, y, flag_file='flags.csv', key='flag', value='selected')

Creates a plot to interactively select and assign flags to data points.

A plot is generated where two variables are plotted, and the user can click on points to assign or remove a flag value to a specified key (column). The flags are stored in a CSV file, which can be used to tag the data points later.

Parameters:

  • df (pandas.DataFrame) – The dataframe containing the data.

  • y (str) – The column name of the y-axis variable.

  • flag_file (str, optional) – The path to the CSV file to store the flags (default is “flags.csv”).

  • key (str, optional) – The column name to assign flags (default is “flag”).

  • value (str, optional) – The value to assign to the key when points are selected (default is “selected”).

Returns:

A VBox widget containing the variable dropdown, add/remove toggle button, the interactive plot, and the output widget.

Return type:

VBox