import pandas as pd
import lux
url = 'https://github.com/lux-org/lux-datasets/blob/master/data/olympic.csv?raw=true'
df = pd.read_csv(url)
df["Year"] = pd.to_datetime(df["Year"], format='%Y') # change pandas dtype for the column "Year" to datetype
In the earlier tutorials, we have seen how Lux recommends visualizations automatically to the user. Often, the user might have a particular visualizations in mind that they want to specify. In this case, users can quickly define their own visualizations using Lux and visualize their data on-demand.
In this tutorial, we will introduce how to create a visualization via the Vis
object and a collection of visualization via the VisList
object.
Vis
¶A Vis
object represents an individual visualization displayed in Lux, which can either be automatically generated or defined by the user.
To generate a Vis
, users should specify their intent and a source dataframe as inputs. The intent is expressed using the same intent specification language described in the last tutorial.
For example, here we indicate our intent for visualizing the Weight
attribute on the dataframe df
.
from lux.vis.Vis import Vis
intent = ["Weight"]
vis = Vis(intent,df)
vis
We can very easily replace the Vis's source data without changing the Vis
definition, which is useful for comparing differences across different datasets with the same schema.
For example, we might be interested in the same Weight
distribution, but plotted only on the subset of data with female athletes.
vis.refresh_source(df[df["Sex"]=='F'])
vis
Likewise, we can modify the intent of the query, in this case, to increase the bin size of the histogram and to indicate the filtered source:
new_intent = [lux.Clause("Weight",bin_size=50),"Sex=F"]
vis.set_intent(new_intent)
vis
Vis
objects are powerful programmatic representations of visualizations that can be exported into visualization code (more in the next tutorial) or be composed into a VisList
collection.
VisList
¶VisList
objects represent collections of visualizations in Lux.
There are two ways to specify lists of visualization in Lux: 1) by specifying intent or 2) by manually composing Vis
object into a list.
VisList
using intent syntax¶First, we look at an example of a VisList
created through a user intent. Here, we create a vis collection of Weight
with respect to all other attributes, using the wildcard "?" symbol.
from lux.vis.VisList import VisList
vc = VisList(["Weight","?"],df)
vc
Alternatively, we can specify desired attributes via a list with respect to Weight
:
vc = VisList(["Weight",['Sport','Year','Height','HostRegion','SportType']],df)
vc
VisList
by constructing Vis
objects¶VisList
can be manually constructed by individually specifying the content of each Vis
, then finally putting the entire list into a VisList
object.
Here is the equivalent VisList
example constructed using this approach:
from lux.vis.VisList import VisList
vcLst = []
for attribute in ['Sport','Year','Height','HostRegion','SportType']:
vis = Vis([lux.Clause("Weight"), lux.Clause(attribute)])
vcLst.append(vis)
vc = VisList(vcLst,df)
vc