После прохождения этих курсов я уверенно создаю профессиональные визуализации и дашборды.
Shoebur RahmanСпециалист по закупкам, Giz Bangladesh
Описание курса
One of the most important tasks of a data scientist is to understand the relationships between their data's physical location and their geographical context. In this course you'll be learning to make attractive visualizations of geospatial data with the GeoPandas package. You will learn to spatially join datasets, linking data to context. Finally you will learn to overlay geospatial data to maps to add even more spatial cues to your work. You will use several datasets from the City of Nashville's open data portal to find out where the chickens are in Nashville, which neighborhood has the most public art, and more!
Предварительные требования
Программа
План курса
1
Building 2-Layer Maps : Combining Polygons and Scatterplots
In this chapter, you will learn how to create a two-layer map by first plotting regions from a shapefile and then plotting location points as a scatterplot.
- Introduction50 XP
- Plotting a scatterplot from longitude and latitude50 XP
- Styling a scatterplot100 XP
- Extracting longitude and latitude100 XP
- Plotting chicken locations100 XP
- Geometries and shapefiles50 XP
- Creating a GeoDataFrame & examining the geometry100 XP
- Plotting shapefile polygons100 XP
- Scatterplots over polygons50 XP
- Geometry50 XP
- Plotting points over polygons - part 1100 XP
- Plotting points over polygons - part 2100 XP
2
Creating and Joining GeoDataFrames
You'll work with GeoJSON to create polygonal plots, learn about projections and coordinate reference systems, and get practice spatially joining data in this chapter.
3
GeoSeries and Folium
First you will learn to get information about the geometries in your data with three different GeoSeries attributes and methods. Then you will learn to create a street map layer using folium.
4
Creating a Choropleth Building Permit Density in Nashville
In this chapter, you will learn about a special map called a choropleth. Then you will learn and practice building choropleths using two different packages: geopandas and folium.
Visualizing Geospatial Data in Python
Курс
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