As a part of the Data Science community, Geospatial data is one of the most crucial kinds of data to work with. The applications are as simple as ‘Where’s my food delivery order right now?’
As a part of the Data Science community, Geospatial data is one of the most crucial kinds of data to work with. The applications are as simple as ‘Where’s my food delivery order right now?’ and as complex as ‘What is the most optimal path for the delivery guy?’
I was recently working on a data science problem involving a lot of gps coordinates. Obviously the very basic question — how do I represent these coordinates on a map in my jupyter notebook? And while we know that plotly, geopy and basemap get the job done, this is the first time I came across Folium and decided to give it a go!
This article is a step by step tutorial on representing your data using folium.
To put it in a one-liner: _**_Manipulate your data in Python, then visualize it in on a Leaflet map via folium.**
Data science is omnipresent to advanced statistical and machine learning methods. For whatever length of time that there is data to analyse, the need to investigate is obvious.
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
You will discover Exploratory Data Analysis (EDA), the techniques and tactics that you can use, and why you should be performing EDA on your next problem.
A data scientist/analyst in the making needs to format and clean data before being able to perform any kind of exploratory data analysis.
Analysis, Price Modeling and Prediction: AirBnB Data for Seattle. A detailed overview of AirBnB’s Seattle data analysis using Data Engineering & Machine Learning techniques.