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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
Introduction to Jupyter Jupyter Python Scripting Jupyter R Scripting Jupyter Julia Scripting Jupyter JavaScript Coding Interactive Widgets Sharing and Converting Jupyter Notebooks Multiuser Jupyter Notebooks Jupyter Scala Jupyter and Big Data

Scala array operations


Scala does not have pandas, but we can emulate some of that logic with our own coding. We will use the same Titanic dataset used in Chapter 2 , Jupyter Python Scripting, from http://www.kaggle.com/c/titanic-gettingStarted/download/train.csv, which we have downloaded in our local space.

We can then use similar coding as was used in Chapter 2 , Jupyter Python Scripting, on pandas:

import scala.io.Source;
val filename = "train.csv"
//PassengerId,Survived,Pclass,Name,Sex,Age,SibSp,
      Parch,Ticket,Fare,Cabin,Embarked
//1,0,3,"Braund, Mr. Owen Harris",male,22,1,0,A/5 21171,7.25,,S
var males = 0
var females = 0
var males_survived = 0
var females_survived = 0
for (line <- Source.fromFile(filename).getLines) {
    var cols = line.split(",").map(_.trim);
    var sex = cols(5);
    if (sex == "male") { 
        males = males + 1;
        if (cols(1).toInt == 1) {
            males_survived = males_survived + 1;
        }
    }
    if (sex == "female") { 
        females...
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