data-mountains
================
<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->
``` python
# 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
``` sh
pip install data_mountains
```
## How to use
``` python
# 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])
```
``` python
# use Altair to create the visual
dm.plot(gdf=gdf, fill='#eee', stroke='#333')
```
Raw data
{
"_id": null,
"home_page": "https://github.com/joel-lbth/data-mountains",
"name": "data-mountains",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.7",
"maintainer_email": "",
"keywords": "nbdev jupyter notebook python",
"author": "joel",
"author_email": "joeldn@pm.me",
"download_url": "https://files.pythonhosted.org/packages/ad/53/b9ac7cda6713742bec1348e1b3157ee0ce8f130d0d7a8e240d3697341be2/data-mountains-0.0.5.tar.gz",
"platform": null,
"description": "data-mountains\n================\n\n<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->\n\n``` python\n# requirements\n\nimport pandas as pd\nimport geopandas as gpd\nfrom shapely.geometry import Polygon, Point, LineString, GeometryCollection\nfrom shapely.ops import unary_union, transform\nimport altair as alt\nimport math\nimport matplotlib.pyplot as plt\n```\n\n## Install\n\n``` sh\npip install data_mountains\n```\n\n## How to use\n\n``` python\n# import the library\nimport data_mountains.mountainise as dm\n\n# some census output area population density data\npopden_oa = pd.read_csv('https://gist.github.com/joel-lbth/b35c0ac7a3652c3f34441d25c45ea84a/raw/d69075dc707b5bdb06c9b640d43db1e5b2ffcb64/lbth_census_2021_pop_density_oa.csv')\n\n# some census output area population weighted centroids\noa = gpd.read_file(\"https://gist.github.com/joel-lbth/00f24602797d51d02d2177ed82f9295d/raw/b6c26621504a0df20ef6db1c93e5f99bce911d0a/lbth_oa21_pop_centroids.geojson\")\n\n# add data attribute to each point by merging on common identifier\ngdf = oa.merge(popden_oa, left_on='oa21cd', right_on='GEOGRAPHY_CODE')\n\n# turn each point in a data sized mountain\ngdf = dm.points_to_peaks(gdf=gdf, column='OBS_VALUE', range=[0, 0.01])\n```\n\n``` python\n# use Altair to create the visual\ndm.plot(gdf=gdf, fill='#eee', stroke='#333')\n```\n\n\n",
"bugtrack_url": null,
"license": "agplv3",
"summary": "turn a geodataframe of points into mountains, scaled by a data attribute associated with each point",
"version": "0.0.5",
"split_keywords": [
"nbdev",
"jupyter",
"notebook",
"python"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "ebfbcd88bf0decdccf70b5eacd583fc4ec69e520561264615286cb377497b277",
"md5": "56c16e5edae2b6c9eb58a8e10d8e9572",
"sha256": "9305ca6e7579295e6b0bce9edb136f1c0129eeea998a1dfbd5c160ef7092802d"
},
"downloads": -1,
"filename": "data_mountains-0.0.5-py3-none-any.whl",
"has_sig": false,
"md5_digest": "56c16e5edae2b6c9eb58a8e10d8e9572",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.7",
"size": 16704,
"upload_time": "2023-01-31T23:54:13",
"upload_time_iso_8601": "2023-01-31T23:54:13.671716Z",
"url": "https://files.pythonhosted.org/packages/eb/fb/cd88bf0decdccf70b5eacd583fc4ec69e520561264615286cb377497b277/data_mountains-0.0.5-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "ad53b9ac7cda6713742bec1348e1b3157ee0ce8f130d0d7a8e240d3697341be2",
"md5": "c0da55f843704c6ddafb7bef088a26ff",
"sha256": "539d9c80d6201958c86d30919c2c01148e2e85d78f8c1d3fa8a36dc010849b61"
},
"downloads": -1,
"filename": "data-mountains-0.0.5.tar.gz",
"has_sig": false,
"md5_digest": "c0da55f843704c6ddafb7bef088a26ff",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.7",
"size": 70104,
"upload_time": "2023-01-31T23:54:16",
"upload_time_iso_8601": "2023-01-31T23:54:16.483014Z",
"url": "https://files.pythonhosted.org/packages/ad/53/b9ac7cda6713742bec1348e1b3157ee0ce8f130d0d7a8e240d3697341be2/data-mountains-0.0.5.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-01-31 23:54:16",
"github": true,
"gitlab": false,
"bitbucket": false,
"github_user": "joel-lbth",
"github_project": "data-mountains",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "data-mountains"
}
JSON
