turn a geodataframe of points into mountains, scaled by a data attribute associated with each point
Project description
data-mountains
# requirements
import pandas as pd
import geopandas as gpd
from shapely.geometry import Polygon, Point, LineString, GeometryCollection
from shapely.ops import unary_union, transform
import altair as alt
import math
import matplotlib.pyplot as plt
Install
pip install data_mountains
How to use
# import the library
import data_mountains.mountainise as dm
# some census output area population density data
popden_oa = pd.read_csv('https://gist.github.com/joel-lbth/b35c0ac7a3652c3f34441d25c45ea84a/raw/d69075dc707b5bdb06c9b640d43db1e5b2ffcb64/lbth_census_2021_pop_density_oa.csv')
# some census output area population weighted centroids
oa = gpd.read_file("https://gist.github.com/joel-lbth/00f24602797d51d02d2177ed82f9295d/raw/b6c26621504a0df20ef6db1c93e5f99bce911d0a/lbth_oa21_pop_centroids.geojson")
# add data attribute to each point by merging on common identifier
gdf = oa.merge(popden_oa, left_on='oa21cd', right_on='GEOGRAPHY_CODE')
# turn each point in a data sized mountain
gdf = dm.points_to_peaks(gdf=gdf, column='OBS_VALUE', range=[0, 0.01])
# use Altair to create the visual
output = dm.plot(gdf=gdf, fill='#eee', stroke='#333')
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
data-mountains-0.0.2.tar.gz
(69.9 kB
view hashes)
Built Distribution
Close
Hashes for data_mountains-0.0.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 018a8f0b314be099856ebfb313ede772ae3e71c68abc4f9807ee88b13e5cef5f |
|
MD5 | b8462c99c0a7e70b5c84da92069417da |
|
BLAKE2b-256 | c7d21905bae6849eb6f45625a7c0dc91e24637362ac79fd091278948446efb20 |