Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
Physics
Chemistry
Biology
Mathematics
English
Economics
Psychology
Social Studies
Fashion Studies
Legal Studies
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
Aligning table to X-axis using matplotlib Python
To align a table to X-axis using matplotlib, we can take the following steps
Steps
Set the figure size and adjust the padding between and around the subplots.
Create a list of data for the dataframe.
Create a tuple for dataframe's columns.
Create a list of rows and values.
Initialize a variable value_increment.
Create a bar plot with the data points.
Put the data into a table.
Set y-label, yticks, xticks, and the title of the plot.
To display the figure, use Show() method.
Example
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams["figure.figsize"] = [7.00, 3.50]
plt.rcParams["figure.autolayout"] = True
data = [
[66386, 174296, 75131, 577908, 32015],
[58230, 381139, 78045, 99308, 160454],
[89135, 80552, 152558, 497981, 603535],
[78415, 81858, 150656, 193263, 69638],
[139361, 331509, 343164, 781380, 52269]
]
columns = ('Freeze', 'Wind', 'Flood', 'Quake', 'Hail')
rows = ['%d year' % x for x in (100, 50, 20, 10, 5)]
values = np.arange(0, 2500, 500)
value_increment = 1000
colors = plt.cm.BuPu(np.linspace(0, 0.5, len(rows)))
n_rows = len(data)
index = np.arange(len(columns)) + 0.3
bar_width = 0.4
y_offset = np.zeros(len(columns))
cell_text = []
for row in range(n_rows):
plt.bar(index, data[row], bar_width, bottom=y_offset, color=colors[row])
y_offset = y_offset + data[row]
cell_text.append(['%1.1f' % (x / 1000.0) for x in y_offset])
colors = colors[::-1]
cell_text.reverse()
the_table = plt.table(cellText=cell_text,
rowLabels=rows,
rowColours=colors,
colLabels=columns,
loc='bottom')
plt.subplots_adjust(left=0.2, bottom=0.2)
plt.ylabel("Loss in ${0}'s".format(value_increment))
plt.yticks(values * value_increment, ['%d' % val for val in values])
plt.xticks([])
plt.title('Loss by Disaster')
plt.show()Output
It will produce the following output −
Updated on: 19-Oct-2021
1K+ Views
Advertisements