The course introduces you to the most essential Geopython Libraries
Perform Spatial Data analysis with Python
Learn the essentials of Geopy,Plotly Library, the workhorse of Geospatial data science in Python.
Learn how to visualize Geospatial data in Python (static and interactive maps)
Learn how to pre-process geospatial data.
Perform Geocoding on Data
8 sections • 37 lectures • 3h 50m total length
Installation of Anaconda Navigator
Datasets & Resources
Extract Latitudes & Longitudes of Data
HeatMap of Restaurants Density
Generate Marker Cluster Analysis of Restaurants & Heatmap of Restaurant Ratings
Automate Your Spatial Analysis
Analyse Average Temperature of country
Analyse Existence of Global Warming
Visualise Average Temperature in Each Season
Analyse Trend In Temperatures for the Top Economies
Perform Spatial analysis on Average Temperature of USA States
Visualise Average temperature of major Indian Cities
Perform Spatial Analysis on Average temperature of major Indian Cities
Datasets & Resources
Reading Data of Covid-19
Choropleth Map of Particular continent
Idea behind Geographical Scatter plot
Geographical Scatter plot for Confirmed Covid-19 Cases
Plotting of Recovery using Choropleth & Geo Scatter plot
Plotting of Deaths using Choropleth & Geo Scatter plot
How to extract Latitudes & Longitudes of a location
Data Preparation For Spatial Analysis
Fetch Geographical Co-ordinates of a country
Idea behind Tileset,Raster & Vector Data
Use-case of Markers
creating a base map
Plot Confirmed Cases using Markers
Plotting of Recovered & Deaths using Markers
Idea behind Geographic Heatmap
Geographic HeatMap of Confirmed Cases
No GIS knowledge is required. We will give breif theoretical explanation as well as its practical implementation
Geospatial data science is a subset of data science that focuses on spatial data and its unique techniques. In this, we are going to perform spatial analysis and trying to find insights from spatial data. In this course, we lay the foundation for a career in Geospatial Data Science. You will get hands-on Geopy, Plotly etc.. the workhorse of Geospatial data science Python libraries.
The topics covered in this course widely touch on some of the most used spatial technique in Geospatial data science. We will be learning how to read spatial data , manipulate and process spatial data using Pandas , and perform some spatial operations. A large portion of the course deals with spatial Visuals like Choropleth, Geographical Scatter plot, Geographical Heatmap, Markers, Geographical HeatMap. Each video contains a summary of the topic and a walkthrough with code examples that will help you learn more effectively.
Who this course is for:
Students who want to become Data Scientist by show-case these Projects on his/her Resume..
Students who like to take their first steps in the Geospatial data science career.
Python users who are interested in Spatial Data Science.
GIS users who are new to python and Jupyter notebooks for Geographic data analysis...
Professionally, I am a Data Scientist having experience of 6 years in finance, retail and transport.From my courses you will straight away notice how I combine my own experience to deliver content in a easiest fashion. To sum up, I am absolutely passionate about Data Analytics and I am looking forward to sharing my own knowledge with you!