Roque Leal

I am a Geographer interested in space-time modeling and its visualizations

To do this, I combine deep data learning, geographic information systems and creative programming to generate innovative and compelling products. Currently my projects focus on business intelligence using optimization tools.

GIS

Experience in the design and implementation of Geographic Information Systems for the oil & gas sector in subsoil and surface modeling.

Planning

Regional studies for the location of projects and their environmental impact, baseline studies and scenario prediction.

Digital Marketing

Analysis of E-commerce data and social media API's for segmentation, geolocation and prediction of audience behavior as an inbound marketing strategy.

Mobile apps

Displaying maps inside of Android and iOS applications with open sources toolset.

Business intelligence

Elt tools modeling, real-time connectivity and business intelligence dashboards for the Oil & Gas and Retail sector.

Data Scientist

Knowledge of creative programming elements for dynamic visualization of spatial models with economic variables, real social media and environment.

I enjoy sharing innovative ideas and techniques in advanced data analysis. I invite you to contact me,

I am looking for new professional challenges with immediate availability to take off your projects 🚀

  • Google Popular Times
    1 DAY AGO

    Google My Business: New York

    This map uses data from Google My Business to display information on popular hours, data on visits and the usual length of visits using anonymized data in real-time to estimate the time. →
  • World Meetup Map 2020
    3 DAYS AGO

    The World Meetup Map 2020

    150 Million people in 330 Thousand Groups an Awesome Map using the Meetup's data to discover the social diversity of humanity: social groups, greatest influencers, popular topics, members and who are its main organizers. →
  • Uber Movement
    7 DAYS AGO

    Uber Movement with street speeds

    A quick glance at the Uber Movement Speeds map of San Francisco from millions of Uber trips using Kepler.gl. →
  • Tripadvisor Chile GeoInsights
    05/23/2020

    Tripadvisor GeoInsights

    A map that combines the data of the Hotels on TripAdvisor using Location Intelligence to visualize the offer of services in Santiago de Chile. →
  • San Francisco Confinement Measures COVID19
    05/23/2020

    Confinement measures and Google Popular Times

    Anonymized data of Google Popular Times to analyze the impact of confinement measures on economic activity. →
  • PowerBi Advertising and Marketing Reporting
    06/05/2020

    Marketing Insights and PowerBI

    E-commerce , ATL Marketing , ATL Media Competitive Analysis , ATL Trends Coronavirus Ecuador , Social Media Reporting , Geomarketing , Location Intelligence
  • Michelin Guide Map
    05/23/2020

    The Michelin Guide Map 2020

    One, two or three stars… The Michelin guide unveiled the distinctions awarded to 2,615 restaurants, find all the awarded establishments on this interactive map. →
  • Prize DataViz
    10/08/2019

    Information is Beautiful Awards 2019

    Five of my projects in the Semifinal round! I invite you to discover the best stories told through the Data. →
  • Tour de France DataScience
    09/12/2019

    #TourdeFrance2019

    Sports are spaces where many emotions converge, especially on Instagram for the #TourdeFrance2019 I have allowed myself to extract the posts and structures in a dynamic and temporary visualization of the interactions. →
  • bringing data to life with powerbi
    08/08/2019

    Bringing data to life

    Invited to the Mapbox Blog, a series of my favorite DataViz to share ideas and how to use data to reveal awesome Geoinsights and communicate innovative ideas. →
  • Waze Dataviz
    06/18/2019

    San Francisco Waze Data

    I have focused on data and opportunities to better understand smart cities, in this example, I am having fun using Waze data with Python and R scripts in Power BI that interact in Visual Mapbox to analyze traffic congestion changes of vehicles in San Francisco over the course of a week. →
  • Oil Map
    02/02/2020

    A global visualization of the Oil & Gas sector

    Host to share and viralize knowledge of the main oil and gas fields in the world. →
  • airbnb datamining
    30/01/2020

    France Airbnb data

    In France, an exploration of users of Airbnb, it is possible to use the data of this social network to discover interesting information, a new vision to understand the real estate market and the tourism sector. →
  • París data
    02/18/2019

    An animated map shows the flow of transport in Paris for a day

    Model of the Paris Metro system developed in Processing thanks to the TransitLand API and Python Pandas libraries🚇. →
  • Uber Mexico Data
    14/08/2019

    Uber Data Analysis CDMX

    Uber data for Mexico City in order to know the dynamics of users and drivers. →
  • Marine Traffic Data
    02/18/2019

    Geopolitics with marinetraffic.com

    This time my curiosity focuses on a global context, analyzing maritime security fears in the Strait of Hormuz, a vital route for the shipment of oil. Using Python and Marine Traffic data are the perfect combination to represent a small part of the routing of oil tankers, identifying the sensitive areas of oil transportation, actors and the timeline of recent tensions in the Gulf. →
  • Migration Data
    12/29/2019

    International Migrant Stock 2019

    Migrations through United Nations data to visualize the Origin-Destination flows using the flowmap.blue to explore the data interactively. →
  • Oil Map
    01/28/2020

    Mapping Machine Learning

    Find an optimal location for a new Italian restaurant in San Francisco, based on #MachineLearning algorithms. The data available at Foursquare grouped using K-means and Mapbox from within a #JupyterNotebook. →
  • Oil Map
    11/15/2019

    Mapbox Developer Spotlight

    On this occasion I allow myself to republish the first review of OilMap on this occasion MapBox and his team share their first impressions of my project; without your help it would not be possible to create amazing maps and visualizations. →
  • Mapping Flickr
    14/11/2019

    Explore your world with Flickr

    Displays a large amount of photos on a highly interactive world map. Explore photos of everyone's places with Flickr. →
  • Properati Data
    01/11/2019

    Real Estate Market in Equator

    A contemporary look at the real estate market for Latam, by analyzing the Properati website, it is possible to know the spatial dynamics of the 54 thousand properties available for Equator. Undoubtedly, a first approach to understand the real estate landscape through an interactive visualization of the data. →
  • Instagram Data
    08/14/2019

    Instagram Location Data # Girod'Italia

    To locate a trend in #Instagram and visualize the relationships on a map, it is possible to program an algorithm and train it with Machine Learning to identify the main posts associated with #GiroDItalia by locating users from the same place where the event occurs and discovering a new way of see this event. →
  • Carto js
    02/15/2019

    Tripadvisor Intelligence Location

    “People who love to eat are always the best people!” For the love of food, I decided to explore TripAdvisor. This visualization includes information about restaurants in Mexico using Python and the power of MapBox and PowerBi. →
  • Retail Machine Learning
    03/23/2020

    Retail Forecast

    The data of 54 stores belonging to an important supermarket network in Equator are analyzed, in order to know the behavior of its customers, propose a grouping model and present a scenario of transaction forecasting. →
  • Dataviz Chile
    06/11/2019

    Data Viz Geospatial Here API

    Regarding Uber and its OpenSource data visualization tools, I share a visualization of the Population Employed in Chile, having as a source a Geodatamining exercise and the exploration of the Here APIs of massive geocoding. →
  • Oil Data Machine Learning
    04/08/2020

    Oil Forecast Prices

    In this Jupyter Notebook, I would like to propose a long-term forecast model of the West Texas Intermediate (WTI) crude oil spot price using the US oil inventory level and based on data hosted on the Energy Information Administration website (EIA). →
  • Big data
    30/12/2019

    Geodatamining and Here APIs

    The data available and for public use on the web are amazing, in this case to represent 20% of the companies registered in the Chilean Internal Revenue Service, using Web scraping techniques with Python and using the Here API for geocoding Massive and advanced results, a total of 120,000 locations. →
  • Carto js
    12/23/2019

    Storytelling Maps

    Telling stories with the data, in Memory of the Disappeared in Argentina, a visualization of a process that we all must remember so that it does not happen again, no doubt in occasions like this, a fact is more than a statistic. →
  • Instagram Data
    09/10/2019

    La Vuelta 2019

    I continue exploring sporting events, this time La Vuelta España 2019, analyzing the associated tags, it is possible to have valuable observations of the interactions of users on Instagram represented in the geographical space. →
  • oil data
    09/11/2018

    #lamarchamasgrande

    A collection of Instagram geoinsights associated with #lamarchamasgrande occurred in Santiago, Chile. →
  • Twitter Data
    12/23/2019

    Twitter location data

    It might be interesting to locate a headmap of tweets for EU. Using the tweepy library to interact with the Twitter API and #PowerBi services, it is possible to create a simple interface to use and discover user interactions, their behavior and different spatial trends. →
  • Uber Bogota Data
    11/19/2019

    Bogotá Uber Data

    A colleague invited me to continue applying models with Uber data so that now I invite you to explore the city of Bogotá to discover its traffic dynamics. →
  • Migration Data
    12/23/2019

    Migration Data

    The phenomenon of migration in South America, causes and projections of this phenomenon are possible to visualize different scenarios using data from the UN, the World Bank and the Foundation for Peace. This time using Python and Pandas, Numpy, GeoPandas and Seaborn libraries based on the System Dynamics model for the study of population dynamics. →
  • python pyspark
    07/19/2019

    PySpark & Streaming Twitter

    Twitter and Spark Together, you get the most popular tweet themes according to a location and according to the volume of Twitter streaming traffic, allowing you to graph different variables of these trends. →
  • Carto Js
    01/04/2019

    Granular Data Guayaquil

    Abstraction of a granular grouping of data to reach a new meaning of spacetime. →
Roque Leal

Contact

  • roqueleal@gmail.com
Your message has been sent shortly, I will answer you

© Roqueleal Copyright. All rights reserved 2020. The photos on this webpage have been provided by pixabay.com and unsplash.com

All product names, trademarks and registered trademarks are property of their respective owners. All company, product and service names used in this website are for identification purposes only. Use of these names,trademarks and brands does not imply endorsement.