bivariate-choropleth 0.0.1

Bivariate Choropleth plotting library

bivariate_choropleth

Usage

Installation

Install latest from the GitHub repository:

$ pip install git+https://github.com/Parkes2/bivariate_choropleth.git

or from conda

$ conda install -c Parkes2 bivariate_choropleth

or from pypi

$ pip install bivariate_choropleth

Documentation

Documentation can be found hosted on this GitHub repository’s pages. Additionally you can find package manager specific guidelines on conda and pypi respectively.

How to use

Choose a palette for your legend

default GridPalette is a 3x3 grid with the blues2reds palette.

Use GridPalette.from_dropdown to get an interactive widget with the premade palettes. See nbs/01_grid_palette for more options for selecting grid palettes

gp = BivariateGridPalette.from_dropdown()

interactive(children=(Dropdown(description='name', options=('blues2reds', 'purple2gold', 'purple2cyan', 'green…

An example using a geodatasets dataset

import geodatasets

geodatasets.data.geoda.atlanta.url

'https://geodacenter.github.io/data-and-lab//data/atlanta_hom.zip'

bivariate_choropleth.shapefiles has some functions for using

from bivariate_choropleth.shapefiles import *

use download_and_unzip to download from the url above. The directory and filename are entered as separate arguments

download_and_unzip(r"https://geodacenter.github.io/data-and-lab//data/",'atlanta_hom.zip')

atlanta_hom.zip already exists, do you want to overwrite y/n? n

calling load_gdf() with no arguments will show a list of folders in the location of SHAPE_FILES_PATH (User/Documents/SHP_FILES)

load_gdf()

Available shapefiles are:  atlanta_hom atlanta_hom LSOA_2021_BOUNDARIES_V4 ca_state ca_counties ca_places

atlanta = load_gdf('atlanta_hom')

from bivariate_choropleth.plotting import *

call plot_bivariate_choropleth(gdf, x_col_name, y_col_name) to plot a bivariate choropleth

ax, cax = plot_bivariate_choropleth(atlanta, x='PE87', y='HR8995')

the grid_size can be changed if you want more ranks in your data.

ax, cax is returned so that the plot can be manipulated

ax, cax = plot_bivariate_choropleth(atlanta, x='PE87', y='HR8995', grid_size=5, palette_name='purple2gold')
ax.set_title('Police Expenditure and Homicide Rates in Atlanta Counties')
ax.set_axis_off()
cax.set_xlabel('Police Expenditure 1987', fontsize=5)
cax.set_ylabel('Homicide Rate 89-95', fontsize=5);