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2021-01-07 12:52:29
30-Day Money-Back Guarantee

This course includes:

  • 4 hours on-demand video
  • 2 articles
  • Full lifetime access
  • Access on mobile and TV
Development Data Science Spatial Analysis

Spatial Analysis & Geospatial Data Science in Python

Learn how to process and visualize geospatial data and perform spatial analysis using Python.
Bestseller
Rating: 4.3 out of 54.3 (36 ratings)
6,333 students
Created by Shan Singh
Last updated 1/2021
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • 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

Course content

8 sections • 37 lectures • 3h 50m total length

  • Preview03:48
  • Preview01:13
  • Installation of Anaconda Navigator
    02:30

  • Datasets & Resources
    00:01
  • Data Pre-Processing
    06:48
  • Extract Latitudes & Longitudes of Data
    13:15

  • HeatMap of Restaurants Density
    08:00
  • Preview01:47
  • Generate Marker Cluster Analysis of Restaurants & Heatmap of Restaurant Ratings
    16:06
  • Automate Your Spatial Analysis
    11:44

  • Analyse Average Temperature of country
    13:29
  • Analyse Existence of Global Warming
    09:58
  • Visualise Average Temperature in Each Season
    13:12
  • Analyse Trend In Temperatures for the Top Economies
    07:35
  • Perform Spatial analysis on Average Temperature of USA States
    16:46
  • Visualise Average temperature of major Indian Cities
    15:57
  • Perform Spatial Analysis on Average temperature of major Indian Cities
    04:56

  • Datasets & Resources
    00:04
  • Reading Data of Covid-19
    06:29

  • Preview03:44
  • Preview07:10
  • Choropleth Map of Particular continent
    04:37
  • Idea behind Geographical Scatter plot
    02:39
  • Geographical Scatter plot for Confirmed Covid-19 Cases
    07:50
  • Plotting of Recovery using Choropleth & Geo Scatter plot
    05:05
  • Plotting of Deaths using Choropleth & Geo Scatter plot
    05:27

  • How to extract Latitudes & Longitudes of a location
    03:42
  • Data Preparation For Spatial Analysis
    04:45
  • Fetch Geographical Co-ordinates of a country
    07:25
  • Idea behind Tileset,Raster & Vector Data
    02:01
  • Use-case of Markers
    02:20
  • creating a base map
    02:52
  • Plot Confirmed Cases using Markers
    04:49
  • Plotting of Recovered & Deaths using Markers
    02:48

  • Preview04:08
  • Idea behind Geographic Heatmap
    01:32
  • Geographic HeatMap of Confirmed Cases
    04:13

Requirements

  • No GIS knowledge is required. We will give breif theoretical explanation as well as its practical implementation

Description

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...

Who this course is for:

  • One who is curious about DataScience

Instructor

Shan Singh
Data Scientist
Shan Singh
  • 4.2 Instructor Rating
  • 416 Reviews
  • 52,769 Students
  • 8 Courses

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!

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