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Learning Jupyter

You're reading from  Learning Jupyter

Product type Book
Published in Nov 2016
Publisher Packt
ISBN-13 9781785884870
Pages 238 pages
Edition 1st Edition
Languages
Author (1):
Dan Toomey Dan Toomey
Profile icon Dan Toomey

Table of Contents (16) Chapters

Learning Jupyter
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
1. Introduction to Jupyter 2. Jupyter Python Scripting 3. Jupyter R Scripting 4. Jupyter Julia Scripting 5. Jupyter JavaScript Coding 6. Interactive Widgets 7. Sharing and Converting Jupyter Notebooks 8. Multiuser Jupyter Notebooks 9. Jupyter Scala 10. Jupyter and Big Data

Python pandas in Jupyter


One of the most widely used features of Python is pandas. It is a third-party library of data analysis packages that can be used freely. In this example, we will develop a Python script that uses pandas to see if there is any effect to using it in Jupyter.

I am using the Titanic dataset from http://www.kaggle.com/c/titanic-gettingStarted/download/train.csv. I am sure the same data is available from a variety of sources.

Here is the Python script that we want to run in Jupyter:

from pandas import *
training_set = read_csv('train.csv')
training_set.head()
male = training_set[training_set.sex == 'male']
female = training_set[training_set.sex =='female']
womens_survival_rate = float(sum(female.survived))/len(female)
mens_survival_rate = float(sum(male.survived))/len(male)

The result is we calculate the survival rates of the Titanic's passengers based on their sex.

We create a new notebook, enter the script into appropriate cells, include adding displays of calculated data...

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