This is a Geospatial Analysis project developed by Felipe Solares da Silva and is part of his professional portfolio.

Data Science examples using NYC Open Data service requests

Code and context for a presentation I gave for Michigan Python on Geopandas.

How to create a choropleth map, assigning your data of interest based on geographical distribution.

A visual representation of a dataset representing natural gas transmission hubs in the contiguous United States.

Wrangled real estate data from multiple sources and file formats, brought it into a single consistent form and analysed the results.

The dataset for thisproject contains information about populated places of the world. The task is to query and find all the capital cities in the World that have a population greater than 1 million and save the resulting subset as a GeoJSON file.

GTFS _LineFrequencies

A simple library to create choropleth maps from geopandas dataframes using mplleaflet

This project delves into an extensive analysis of 311 service requests made by Boston residents in 2021. It aims to uncover patterns, trends, and crucial insights from the dataset, shedding light on complaint categories, request sources, locations, and government handling.

Explore geospatial data analysis through diverse projects. Gain insights into mapping, visualization, and location-based analytics in this repository focused on practical applications and solutions.

Data-Product-Management

Portafolio of Python on Machine Learning and Deep Learining proyects

Performing GeoSpatial Data Science on PostGIS-hosted data through Jupyter Notebooks

Aprendendo a tratar dados georreferenciados

Using OSMnx, OSRM, and Google Maps Directions API with Python to calculate shortest, fastest, and traffic-based most-efficient routes for a set of origin and destination points

Visualization project with use of GeoPandas and Bokeh libraries. The aim is to show map of french communes where avalanche accidents occured the most often in last 10 years.