Time: The time of day on which the incident occurredД§. Date: The Date on which the incident occurredД¦. DayOfWeek: The day of week on which the incident occurredДҐ. Descript: Description of the crime or incidentД¤. Category: Category of crime or incidentДЈ. The resulting data frame has 100 reported crimes as rows and each row consists of 13 features/attributes:Дў. There is a detailed jupyter notebook on the same. However for the details steps involved in data wrangling please use the below mention link to my GitHub account. IвЂ™m going to skip the data wrangling part as the article is more focused on Map visualisation. Incidents derived from San Francisco Police Department (SFPD) Crime Incident Reporting system. DatasetsДЇor the purpose of this article, I have used the San Francisco Police Department Incidents for the year 2016В data from San Francisco public data portal. For this section we are going to use the 'San Francisco Police Department Incidents for the year of 2016'. The layers on the map can be any reasonable data which details or define a geography. This is a very important feature that is used widely for creating maps with layers. Below is a world map created using Folium. What is attractive aboutВ FoliumВ maps is that they are interactive, so you can zoom into any region of interest despite the initial zoom level. You simply create aВ Folium MapВ object and then you display it. Generating the world map is straight forward inВ Folium. Folium supports both GeoJSON and TopoJSON overlays, as well as the binding of data to those overlays to create choropleth maps with color-brewer color schemes. The library has a number of built-in tilesets from OpenStreetMap, Mapbox, and Stamen, and supports custom tilesets with Mapbox or Cloudmade API keys. It enables both the binding of data to a map for choropleth visualisations as well as passing Vincent/Vega visualisations as markers on the map. Manipulate your data in Python, then visualize it in on a Leaflet map via Folium.ДЇolium makes it easy to visualize data that's been manipulated in Python on an interactive Leaflet map. The fact that the Folium results are interactive makes this library very useful for dashboard building.ДЇrom the official Folium documentation page:ДЇolium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the Leaflet.js library. INTRODUCTION TO FOLIUMДЇolium is a powerful Python library that helps you create several types of Leaflet maps. Folium, on the other hand, is completely free. While other libraries are available to visualise geospatial data, such as plotly, they might have a cap on how many API calls you can make within a defined time frame. What is nice about FoliumВ is that it was developed for the sole purpose of visualising geospatial data. This article is an attempt to show few geospatial data visualisation options in Python using Folium. The way we understand and use geospatial data today has completely revolutionised data analytics and business intelligence. However, in the world of technology, maps are becoming principal tools to analyse data for every industry vertical. A world map has always inspired wanderlust in me.

Folium maps python