Visualizing Spatial Data

1. ArcGIS API for Python

The ArcGIS API for Python, i.e., the arcgis package, is a powerful, modern and easy to use Pythonic library to perform GIS visualization and analysis, spatial data management and GIS system administration tasks that can run both in an interactive fashion, and using scripts.

The package is shipped with a standard ArcGIS Pro installation. The API is distributed as the arcgis package via conda and pip. Within the arcgis package, which represents the generic GIS model, functionality is organized into a number of different modules that makes it simple to use and understand. Each module has a handful of types and functions that are focused towards one aspect of the GIS.

This diagram below depicts the modules present in the API.

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1.1 Import the package

The following statement imports the arcgis library and several submodules that we use for to plotting maps in a Python Notebook.

import arcgis
from arcgis import GIS, GeoAccessor, GeoSeriesAccessor, pd

1.2 The arcgis.GIS class

What is class in Python?

• It is a blueprint for building things (a machine produces products)

• Things get created from the class are called objects (or instances of the class)

• DRY (Don’t repeat yourself) code.

• Example classes: a college student or a car, or a data structure that organizes the data just as np.ndarray and pd.DataFrame.

What is GIS (Geographic Information System)?

• Geographic Data:

  • collection

  • storage

  • manipulation

  • analysis

  • visualization

  • management/administration

  • distribution

• A variety of technologies:

  • human activities (such as conducting survey of an area of land)

  • hardware

  • software (a narrower definition of GIS)

The arcgis.GIS:

• a portal to do GIS in Python Notebooks

• can link to an ArcGIS Online account

• or, be used locally without the connection

2. Spatially Enabled DataFrame

A Spatially Enabled DataFrame (SEDF) is a special type of pd.DataFrame that is part of the ArcGIS API for Python. It allows you to work with and analyze spatial data in Python, using the power of the Pandas library.

It is a class defined in the features module of arcgis (arcgis.features). It contains types and functions for working with features and feature layers in the GIS. Since it is an extension of pd.DataFrame class, meaning that it possesses all functions of a normal DataFrame.

We use ArcPy as the geometry engine for this module, which gives us access to all native GIS data ArcGIS Pro supports.

Now, let’s see how we can load a feature class as a “SEDF.”

from arcgis import pd, GeoAccessor, GeoSeriesAccessor
import arcpy

gdb_worksp = r"..\data\class_data.gdb"
arcpy.env.workspace = gdb_worksp
blkgrp_fc = "blockgroups"

blkgrp_sedf = pd.DataFrame.spatial.from_featureclass(blkgrp_fc)
blkgrp_sedf.head()

	OBJECTID	STATEFP10	COUNTYFP10	TRACTCE10	BLKGRPCE10	GEOID10	NAMELSAD10	MTFCC10	FUNCSTAT10	ALAND10	...	DEN_NOTWEL	DEN_NOTATA	PCT_OWN5	PCT_RENT5	PCT_BACHLR	PCT_POV	PCT_RU1	DATAYEAR	DESCRIPT	SHAPE
0	1	12	023	110903	2	120231109032	Block Group 2	G5030	S	57546992	...	0.004918	0.0	17.225951	62.878788	9.922481	23.488372	23.488372	REDISTRICTING, SF1, ACS 2010	120231109032	{"rings": [[[530441.2199999988, 651631.75], [5...
1	2	12	023	110904	1	120231109041	Block Group 1	G5030	S	85591551	...	0.000329	0.000329	26.21232	58.015267	5.456656	4.102167	4.102167	REDISTRICTING, SF1, ACS 2010	120231109041	{"rings": [[[534712.1700000018, 663369.54], [5...
2	3	12	007	000300	5	120070003005	Block Group 5	G5030	S	196424609	...	0.000021	0.0	13.270142	68.181818	1.254613	10.701107	10.701107	REDISTRICTING, SF1, ACS 2010	120070003005	{"rings": [[[567924.9299999997, 665800.79], [5...
3	4	12	007	000300	4	120070003004	Block Group 4	G5030	S	16339411	...	0.0	0.0	18.924731	73.71134	12.617839	14.902103	14.902103	REDISTRICTING, SF1, ACS 2010	120070003004	{"rings": [[[588576.3599999994, 644359.46], [5...
4	5	12	007	000300	1	120070003001	Block Group 1	G5030	S	57089369	...	0.0	0.001138	22.957198	43.333333	1.134021	21.161826	21.161826	REDISTRICTING, SF1, ACS 2010	120070003001	{"rings": [[[576256.1799999997, 656541.8300000...

5 rows × 202 columns

print(len(blkgrp_sedf))
print(blkgrp_sedf.shape)

178
(178, 202)

blkgrp_sedf['TOTALPOP'].values

<IntegerArray>
[2094, 2269, 1305, 1991, 2056, 1410, 1890, 2510, 1150, 1856,
 ...
 1091,  637,  921, 1342, 2680, 1211, 1788, 1723, 1189,  789]
Length: 178, dtype: Int32

3. Visualizing spatial data

3.1 Create a map object

Before we can create a map, we need to set up a GIS instance that is connected to your ArcGIS Online account.

my_gis = GIS()

my_gis

GIS @ https://www.arcgis.com

Then, we can prepare SEDFs Loading data into the GIS instance

import arcpy
gdb_worksp = r"..\data\class_data.gdb"
arcpy.env.workspace = gdb_worksp

blkgrp = "blockgroups"
schools = 'schools'

blkgrp_sedf = pd.DataFrame.spatial.from_featureclass(blkgrp)
schools_sedf = pd.DataFrame.spatial.from_featureclass(schools)

Use the map() function to create a map widget from the GIS instance to create a map.

The location parameter takes a list of coordinates. And zoomlevel dictates how “zoomed-in” the map will be displayed initially. It is a value ranged between 0 (world) to 23 (house). Check this link to learn more.

my_map_in_my_gis = my_gis.map(location=[29.7, -82.3],
                              zoomlevel=9)

my_map_in_my_gis

3.2 Load SEDFs into the MapWidget

Call spatial.plot() and specify the map_widget parameter to add the layer to a specific map. Note that SEDF loaded later will overlap the SEDFs loaded earlier.

blkgrp_sedf.spatial.plot(map_widget=my_map_in_my_gis)

schools_sedf.spatial.plot(map_widget=my_map_in_my_gis,
                          col='NAME', 
                          renderer_type='u')

my_map_in_my_gis

3.3 Modify the size of the widget window

from ipywidgets import Layout

my_map_in_my_gis.layout = Layout(height="600px")
my_map_in_my_gis

my_map_in_my_gis.layout = Layout(width="600px", height="600px")
my_map_in_my_gis

3.3 Change the Basemap

1. basemaps attribute of a map returns a list of available basemaps

my_map_in_my_gis.basemaps

['dark-gray-vector',
 'gray-vector',
 'hybrid',
 'oceans',
 'osm',
 'satellite',
 'streets-navigation-vector',
 'streets-night-vector',
 'streets-relief-vector',
 'streets-vector',
 'terrain',
 'topo-vector']

Pick a basemap from the above list and assign it to the basemap attribute to the map widget.

my_map_in_my_gis.basemap = 'dark-gray-vector'
my_map_in_my_gis

3.4 Choropleth Map

A choropleth map is a type of thematic map that uses color to represent a quantitative variable (e.g., population) for different geographic regions, such as countries, states, or counties.

In a choropleth map, each region is shaded or colored based on its corresponding value for the variable being mapped. Regions with higher values are typically shaded with darker or more intense colors, while regions with lower values are shaded with lighter or less intense colors.

ArcGIS Python API provides a series of color maps to plot features on maps.

from arcgis import mapping

mapping.display_colormaps()

map2 = my_gis.map(location=[29.7, -82.3], zoomlevel=9)

blkgrp_sedf.spatial.plot(map_widget=map2,
                         colors="YlGnBu",
                         col='TOTALPOP',
                         renderer_type='c',
                         method='esriClassifyNaturalBreaks',
                         class_count=7)
map2.layout = Layout(height="700px")
map2.basemap = "dark-gray-vector"
map2