2.3 Comparing Plotting Libraries and Declarative Visualizations

from plotnine import *
from matplotlib import pyplot as plt
from plotnine import data
import plotly.express as px
import seaborn as sns

mpg = data.mpg

Bar Chart

mpg

	manufacturer	model	displ	year	cyl	trans	drv	cty	hwy	fl	class
0	audi	a4	1.8	1999	4	auto(l5)	f	18	29	p	compact
1	audi	a4	1.8	1999	4	manual(m5)	f	21	29	p	compact
2	audi	a4	2.0	2008	4	manual(m6)	f	20	31	p	compact
3	audi	a4	2.0	2008	4	auto(av)	f	21	30	p	compact
4	audi	a4	2.8	1999	6	auto(l5)	f	16	26	p	compact
...	...	...	...	...	...	...	...	...	...	...	...
229	volkswagen	passat	2.0	2008	4	auto(s6)	f	19	28	p	midsize
230	volkswagen	passat	2.0	2008	4	manual(m6)	f	21	29	p	midsize
231	volkswagen	passat	2.8	1999	6	auto(l5)	f	16	26	p	midsize
232	volkswagen	passat	2.8	1999	6	manual(m5)	f	18	26	p	midsize
233	volkswagen	passat	3.6	2008	6	auto(s6)	f	17	26	p	midsize

234 rows × 11 columns

# Pandas
(mpg['manufacturer']
 .value_counts(sort=False)
 .plot.barh()
 .set_title('Number of Cars by Make')
)

Text(0.5, 1.0, 'Number of Cars by Make')

# Plotnine (ggplot2 clone)
(ggplot(mpg) + 
   aes(x='manufacturer') +
   geom_bar() + 
   coord_flip() +
   ggtitle('Number of Cars by Make')
)

fig = px.bar(
    mpg.groupby('manufacturer', observed=False).size().reset_index(name='count'),
    x='count',
    y='manufacturer',
    orientation='h',
    title='Number of Cars by Make',
)

fig

Scatter Plot

(mpg.
    plot.
    scatter(x='displ', y='hwy'))

<Axes: xlabel='displ', ylabel='hwy'>

mpg

	manufacturer	model	displ	year	cyl	trans	drv	cty	hwy	fl	class
0	audi	a4	1.8	1999	4	auto(l5)	f	18	29	p	compact
1	audi	a4	1.8	1999	4	manual(m5)	f	21	29	p	compact
2	audi	a4	2.0	2008	4	manual(m6)	f	20	31	p	compact
3	audi	a4	2.0	2008	4	auto(av)	f	21	30	p	compact
4	audi	a4	2.8	1999	6	auto(l5)	f	16	26	p	compact
...	...	...	...	...	...	...	...	...	...	...	...
229	volkswagen	passat	2.0	2008	4	auto(s6)	f	19	28	p	midsize
230	volkswagen	passat	2.0	2008	4	manual(m6)	f	21	29	p	midsize
231	volkswagen	passat	2.8	1999	6	auto(l5)	f	16	26	p	midsize
232	volkswagen	passat	2.8	1999	6	manual(m5)	f	18	26	p	midsize
233	volkswagen	passat	3.6	2008	6	auto(s6)	f	17	26	p	midsize

234 rows × 11 columns

(mpg
 .plot
 .scatter(x='displ', y='hwy')
 .set(title='Engine Displacement in Liters vs Highway MPG',
      xlabel='Engine Displacement in Liters',
      ylabel='Highway MPG'));

(ggplot(mpg) +
    aes(x = 'displ', y = 'hwy') +
    geom_point() + 
    ggtitle('Engine Displacement in Liters vs Highway MPG') +
    xlab('Engine Displacement in Liters') +
    ylab('Highway MPG')
)

fig = px.scatter(
    mpg,
    x='displ',
    y='hwy',
    title='Engine Displacement in Liters vs Highway MPG',
    labels={
        'displ': 'Engine Displacement in Liters',
        'hwy': 'Highway MPG'
    }
)

fig.show()

Scatter Plot, Faceted with Color

for c, df in mpg.groupby('class'):
    plt.scatter(df['displ'], df['hwy'], label=c)

fig, ax = plt.subplots()
for c, df in mpg.groupby('class'):
    plt.scatter(df['displ'], df['hwy'], label=c)

fig, ax = plt.subplots()
for c, df in mpg.groupby('class'):
    ax.scatter(df['displ'], df['hwy'], label=c)
ax.legend()
ax.set_title('Engine Displacement in Liters vs Highway MPG')
ax.set_xlabel('Engine Displacement in Liters')
ax.set_ylabel('Highway MPG')

Text(0, 0.5, 'Highway MPG')

(sns
 .FacetGrid(mpg, hue='class', height=5)
 .map(plt.scatter, 'displ', 'hwy')
 .add_legend()
 .set(
    title='Engine Displacement in Liters vs Highway MPG',
    xlabel='Engine Displacement in Liters',
    ylabel='Highway MPG'
))

<seaborn.axisgrid.FacetGrid at 0x3233bbe50>

(ggplot(mpg) + 
    aes(x = 'displ', y = 'hwy', color = 'class') +
    geom_point() + 
    ggtitle('Engine Displacement in Liters vs Highway MPG') +
    xlab('Engine Displacement in Liters') +
    ylab('Highway MPG'))

fig = px.scatter(
    mpg,
    x='displ',
    y='hwy',
    color='class',
    title='Engine Displacement in Liters vs Highway MPG',
    labels={
        'displ': 'Engine Displacement in Liters',
        'hwy': 'Highway MPG',
        'class': 'Vehicle Class'
    }
)

fig.show()