missing-data-as-shadows 1.0.3

Vizualize missing data as shadows

Visualization of Incomplete Datasets

This project focuses on visualizing incomplete datasets, where missing data is represented using shadows or other graphical elements. The goal is to facilitate the interpretation of missing values and help analysts gain a deeper understanding of the data.

Usage

import pandas as pd

from missing_data_as_shadows import make_full_analysis, scatter_with_shadows_rect_binned

Load data with missing values

df = pd.read_csv('data.csv')

Generate full visualization

make_full_analysis(df, output_name="output_name", method="spearman")

Method parameter is correlation method

If you don't provide method parameter default is pearson.

The method parameter allows you to select any correlation method supported by pandas, such as:

• pearson

• kendall

• spearman

Generate Subplots with Shadows for Two Attributes

create_subplot_with_shadows(data, atr1, atr2, name="test", save=True)

Parameters

data (DataFrame) – The dataset containing the attributes to visualize.

atr1 (str) – The first attribute (column name) for visualization.

atr2 (str) – The second attribute (column name) for visualization.

name (str, optional, default=None) – The filename to save the plot. If None, the plot will not be saved.

Generate visualization for two chosen attributes

Usage

scatter_with_shadows_rect_binned(

diabetesData,
diabetes_data_attribute_one, 
diabetes_data_attribute_two,
bins_count=10,
marker_size_scatter=3,
marker_size_rect=0.001
name="Name"

)

Parameters

df (DataFrame) – The dataset containing the attributes to visualize.

col_a (str) – The first attribute (column name) to be plotted on the x-axis.

col_b (str) – The second attribute (column name) to be plotted on the y-axis.

marker_size_scatter (float, default=3) – The size of scatter plot markers.

marker_size_rect (float, default=0.5) – The size of markers for binned data representation.

bins_count (int, default=10) – The number of bins used for shadow visualization.

fraction_of_range (float, default=0.5) – Determines the proportion of the attribute range considered for binning.

color_missing_a (str, default='grey') – Color used to highlight missing values in col_a.

color_missing_b (str, default='grey') – Color used to highlight missing values in col_b.

alpha_main (float, default=0.3) – Transparency level of the scatter points.

outline_color (str, default='black') – Color of the outline around data points.

outline_width (float, default=0.5) – Thickness of the outline around data points.

name - (str) - save with specified name