numeric_numeric_summary

numeric_numeric_summary(data: DataFrame, column1: str, column2: str, fig_height: int = 1200, fig_width: int = 1200, trend_line: str = 'auto', opacity: float = 1.0, hist_bins: Optional[int] = None, lower_quantile1: float = 0, upper_quantile1: float = 1, lower_quantile2: float = 0, upper_quantile2: float = 1, num_intervals: int = 4, interval_type: str = 'quantile', transform1: str = 'identity', transform2: str = 'identity', display_figure: bool = False) → Figure

Creates a bivariate EDA summary for two numeric data columns in a pandas DataFrame.

Parameters

• data – pandas DataFrame to perform EDA on

• column1 – name of numeric column to plot as independent variable

• column2 – name of numeric column to plot as dependent variable

• fig_height – Height of the plot in pixels

• fig_width – Width of the plot in pixels

• opacity – Level of opacity to apply to points in scatterplot (0 = fully transparent, 1 = fully opaque)

• trend_line – Trend line to plot over data. Default is to plot no trend line. Other options are passed to geom_smooth.

• hist_bins – Number of bins to use for the histogram. Default will use plotly defaults

• lower_quantile1 – Lower quantile to filter data above for column1

• upper_quantile1 – Upper quantile to filter data below for column1

• lower_quantile2 – Lower quantile to filter data above for column2

• upper_quantile2 – Upper quantile to filter data below for column2

• num_intervals – Number of intervals to bin column1 into for the boxplots

• interval_type – Type of intervals to bin column1 into for the boxplots. ‘quantile’ or ‘equal width’

• transform1 –

  Transformation to apply to the column1 for plotting:

  • ’identity’: no transformation

  • ’log’: apply a logarithmic transformation (zero and negative values will be filtered out)

  • ’sqrt’: apply a square root transformation

• transform2 – Transformation to apply to the column2 data for plotting. Same options as for column1.

• display_figure – Whether to display the figure in addition to returning it