Goal¶

This post aims to introduce examples of visualization by Plotly Express.

The followings are introduced:

Prepared example data
Scatter plot
- basic
- basic + size
- basic + size + color
- basic + size + color + time
- heatmap + histogram

2019-07-19 21-54-58 2019-07-19 21_56_00_gapminder_plotly_express

Reference

Libraries¶

In [8]:

import pandas as pd
import numpy as np
import plotly_express as px
import plotly.io as pio
pio.renderers.default = "png"

Load a prepared data¶

In [2]:

df = px.data.carshare()
df.head()

Out[2]:

	centroid_lat	centroid_lon	car_hours	peak_hour
0	45.471549	-73.588684	1772.750000	2
1	45.543865	-73.562456	986.333333	23
2	45.487640	-73.642767	354.750000	20
3	45.522870	-73.595677	560.166667	23
4	45.453971	-73.738946	2836.666667	19

Tips¶

In [3]:

df = px.data.tips()
df.head()

Out[3]:

	total_bill	tip	sex	smoker	day	time	size
0	16.99	1.01	Female	No	Sun	Dinner	2
1	10.34	1.66	Male	No	Sun	Dinner	3
2	21.01	3.50	Male	No	Sun	Dinner	3
3	23.68	3.31	Male	No	Sun	Dinner	2
4	24.59	3.61	Female	No	Sun	Dinner	4

Election¶

In [4]:

df = px.data.election()
df.head()

Out[4]:

	district	Coderre	Bergeron	Joly	total	winner	result
0	101-Bois-de-Liesse	2481	1829	3024	7334	Joly	plurality
1	102-Cap-Saint-Jacques	2525	1163	2675	6363	Joly	plurality
2	11-Sault-au-Récollet	3348	2770	2532	8650	Coderre	plurality
3	111-Mile-End	1734	4782	2514	9030	Bergeron	majority
4	112-DeLorimier	1770	5933	3044	10747	Bergeron	majority

Wind¶

In [5]:

df = px.data.wind()
df.head()

Out[5]:

	direction	strength	frequency
0	N	0-1	0.5
1	NNE	0-1	0.6
2	NE	0-1	0.5
3	ENE	0-1	0.4
4	E	0-1	0.4

Gap Minder¶

In [6]:

df = px.data.gapminder()
df.head()

Out[6]:

	country	continent	year	lifeExp	pop	gdpPercap	iso_alpha	iso_num
0	Afghanistan	Asia	1952	28.801	8425333	779.445314	AFG	4
1	Afghanistan	Asia	1957	30.332	9240934	820.853030	AFG	4
2	Afghanistan	Asia	1962	31.997	10267083	853.100710	AFG	4
3	Afghanistan	Asia	1967	34.020	11537966	836.197138	AFG	4
4	Afghanistan	Asia	1972	36.088	13079460	739.981106	AFG	4

Scatter Plot¶

Basic Scatter plot¶

In [10]:

px.scatter(df, x='gdpPercap', y='lifeExp', width=900, height=400)

Scatter plot + size¶

In [11]:

px.scatter(df, x='gdpPercap', y='lifeExp', size='pop', width=900, height=400)

Scatter plot + size + color¶

In [12]:

px.scatter(df, x='gdpPercap', y='lifeExp', size='pop', color='country', width=900, height=400)

Scatter plot + size + color + time¶

In [13]:

px.scatter(df, x='gdpPercap', y='lifeExp', size='pop', color='country', animation_frame='year', width=900, height=400)

In [14]:

px.density_heatmap(df, x="gdpPercap", y="lifeExp", marginal_y="histogram", marginal_x="histogram")