Space
What graphs will we see today?
Variable #1 | Variable #2 | Chart Names | Chart Shape |
---|---|---|---|
Quant | Qual | Choropleth and Symbols Maps, Cartograms |
|
Inspiration
How do these Chart(s) Work?
In Figure 1 (a), we have a choropleth map. What does choropleth1 mean? And what kind of information could this map represent? The idea is to colour a specific area of the map, a district or state, based on a Quant or a Qual variable.
The Figure 1 (b) deliberately distorts and scales portions of the map in proportion to a Quant variable, in this case, population in 2018.
In Figure 2 (a) and Figure 2 (b), symbols are used to indicate either the location/presence of an item of interest, or a quantity by scaling their size in proportion to a Quant variable
Creating Maps
Let us use a built-in dataset in Orange to create a Symbol/bubble/Choropleth map. This dataset pertains to the climate in several European cities. Here is the workflow:
Let us look first at the data table.
Data Dictionary
-
City
: City in Europe -
Climate
: One of six types:oceanic
,meditterranean
,humid
…etc. -
Climate(koppen)
: Some sort of climate classification(acronym?)
Quantitative Data
- All other variables are Quantitative. These pertain to temperature,rainfall, humidity, sunshine, and ultraviolet radiation.
-
Longitude
andLatitude
are also Quant
Note the presence of specific Longitude Latitude columns in the data. Why am I saying this in that peculiar order ??💭
We have directed the output of the Data Table
widget to the Geo Map
widget, so that the selected citie(s) show up as symbols on the map. The symbol colour is proportional to one of the other “non-locational” Quant variables. It can also be a Qual variable.
We can also connect the same output to the Choropleth Map
widget. However in this case, Orange colours the country in which the chosen city is located, based on the selected Quant/Qual variable for colour.
Note how Orange “gets hold” of a base map of Europe to plot the cities on. These are built-in datasets / automatically downloaded by Orange using free map services such as Open Street Map
Nopes.
Symbol Maps: https://academy.datawrapper.de/category/278-symbol-maps
Choropleth Maps: https://academy.datawrapper.de/category/93-maps
Dataset: UFO Sightings
Suppose we have our own data, of places we have visited. Let us cook up such a dataset manually (in Excel) without Long and Lat, and we can then Geo Code
the places plot them based on some other parameter of interest.
Geocoding widget extracts latitude/longitude pairs from region names or synthesizes latitude/longitude to return region name. If the region is large, say a country, encoder with return the latitude and longitude of geometric centre.
Here is a Excel to download; you should plot this first and then edit the places and its characteristics to suit your own research.
Note that this dataset does have longitude and latitude data. We will import this into Orange and deliberately Geo Code
this, just to compare.
Examine the Data
Dataset: Animal Migration Tracks
So far we have seen maps that place POINTS on a base map. Let us see if we can get tracks to show…or not, peasants.
Examine the Data
Data Dictionary
Research Questions
What is the Story Here?
Your Turn
Wait, But Why?
References
Footnotes
Etymology. From Ancient Greek χώρα (khṓra, “location”) + πλῆθος (plêthos, “a great number”) + English map. First proposed in 1938 by American geographer John Kirtland Wright to mean “quantity in area,” although maps of the type have been used since the early 19th century.↩︎