Skip to main content

# Geo-localized data in Brazil

Python lib for easily dealing with Geo-localized Data in Brazil

We have implemented more than 200 dimensions of geolocalized data from www.atlasbrasil.org.br

It contains a detailed set of demographic information such as gender, age, income, education, inequality and many other interesting things.

# Installation

## Installing the geo_data_br lib

First install [geopandas](http://geopandas.org/install.html) using conda:

conda install geopandas

Then,

pip3 install geo_data_br

# Features

## Getting data from list of points

Given a list of latitude and longitude points we can use the lib to retrieve the corresponding data.

import geo_data_br.points points_of_interest = [(-59.23352, -3.35030), (-60.17875, -3.27442)] demographics_on_poi = geo_data_br.points.data_on_points(points_of_interest) demographics_on_poi.gini >>> 0 0.59 >>> 1 0.51 >>> Name: gini, dtype: float64

demographics_on_poi.espvida >>> 0 72.91 >>> 1 68.70 >>> Name: espvida, dtype: float64

# Contributing

Metadata

Release files for geo-data-br 0.3.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for geo-data-br 0.3.5
File Size Uploaded Provenance Actions
geo_data_br-0.3.5.tar.gz 15.4 MB Without provenance Details for geo_data_br-0.3.5.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for geo-data-br 0.3.5
File Interpreter ABI Platform Actions
geo_data_br-0.3.5-py3-none-any.whl Python 3 none any Details for geo_data_br-0.3.5-py3-none-any.whl

Total release size: 15.4 MB

Release files / geo_data_br-0.3.5.tar.gz

Download URL geo_data_br-0.3.5.tar.gz
Size 15.4 MB
Tags Source
SHA-256 checksum
How to use checksums
4bda89bbcbff575d14585490c7bd8c3f17c6032c4a114f33198ac20a75485f0b
BLAKE2b-256 checksum
How to use checksums
ae55f1ff19001372938f60fda5ded4169d31689a18bddb6ee8be438fb35c5f59
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.35.0 CPython/3.7.3

Release files / geo_data_br-0.3.5-py3-none-any.whl

Download URL geo_data_br-0.3.5-py3-none-any.whl
Size 5.6 kB
Tags Python 3
SHA-256 checksum
How to use checksums
23d4c97eb076c37a345d1c5c5224760e147d2286ebb000e7708a65b9d6f4bec6
BLAKE2b-256 checksum
How to use checksums
06e03567892dcda41f268635f275757de680edcb3646a250377a884a1f3026a6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.35.0 CPython/3.7.3

Security for geo-data-br 0.3.5

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page