Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
Arrow up icon
GO TO TOP
Python Data Analysis

You're reading from   Python Data Analysis Perform data collection, data processing, wrangling, visualization, and model building using Python

Arrow left icon
Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781789955248
Length 478 pages
Edition 3rd Edition
Languages
Arrow right icon
Authors (2):
Arrow left icon
 Navlani Navlani
Author Profile Icon Navlani
Navlani
Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
Arrow right icon
View More author details
Toc

Table of Contents (20) Chapters Close

Preface 1. Section 1: Foundation for Data Analysis
2. Getting Started with Python Libraries FREE CHAPTER 3. NumPy and pandas 4. Statistics 5. Linear Algebra 6. Section 2: Exploratory Data Analysis and Data Cleaning
7. Data Visualization 8. Retrieving, Processing, and Storing Data 9. Cleaning Messy Data 10. Signal Processing and Time Series 11. Section 3: Deep Dive into Machine Learning
12. Supervised Learning - Regression Analysis 13. Supervised Learning - Classification Techniques 14. Unsupervised Learning - PCA and Clustering 15. Section 4: NLP, Image Analytics, and Parallel Computing
16. Analyzing Textual Data 17. Analyzing Image Data 18. Parallel Computing Using Dask 19. Other Books You May Enjoy

Plotting a simple graph

Let's plot a first and simple plot using Bokeh. First, we need to import the basic bokeh.plotting module. The output_notebook() function defines that the plot will render on the Jupyter Notebook. The figure object is used as one of the core objects to draw charts and graphs. The figure object focuses on the plot title, size, label, grids, and style. The figure object also deals with plot style, title, axes labels, axes, grids, and various methods for adding data:

# Import the required modules
from bokeh.plotting import figure
from bokeh.plotting import output_notebook
from bokeh.plotting import show

# Create the data
x = [1,3,5,7,9,11]
y = [10,25,35,33,41,59]

# Output to notebook
output_notebook()

# Instantiate a figure
fig= figure(plot_width = 500, plot_height = 350)

# Create scatter circle marker plot by rendering the circles
fig.circle(x, y, size = 10, color = "red", alpha = 0.7)

# Show the plot
show(fig)

This results in the following output...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €14.99/month. Cancel anytime
Visually different images