Master core data analysis skills using Julia. Interesting hands-on
projects guide you through time series data, predictive models,
popularity ranking, and more. In Julia for Data Analysis you will
learn how to: Read and write data in various formats Work with
tabular data, including subsetting, grouping, and transforming
Visualize your data Build predictive models Create data processing
pipelines Create web services sharing results of data analysis
Write readable and efficient Julia programs Julia was designed for
the unique needs of data scientists: it's expressive and
easy-to-use whilst also delivering super-fast code execution. Julia
for Data Analysis shows you how to take full advantage of this
amazing language to read, write, transform, analyze, and visualize
data--everything you need for an effective data pipeline. It's
written by Bogumil Kaminski, one of the top contributors to Julia,
#1 Julia answerer on StackOverflow, and a lead developer of Julia's
core data package DataFrames.jl. Its engaging hands-on projects get
you into the action quickly. Plus, you'll even be able to turn your
new Julia skills to general purpose programming! Foreword by Viral
Shah. Purchase of the print book includes a free eBook in PDF,
Kindle, and ePub formats from Manning Publications. About the
technology Julia is a great language for data analysis. It's easy
to learn, fast, and it works well for everything from one-off
calculations to full-on data processing pipelines. Whether you're
looking for a better way to crunch everyday business data or you're
just starting your data science journey, learning Julia will give
you a valuable skill. About the book Julia for Data Analysis
teaches you how to handle core data analysis tasks with the Julia
programming language. You'll start by reviewing language
fundamentals as you practice techniques for data transformation,
visualizations, and more. Then, you'll master essential data
analysis skills through engaging examples like examining currency
exchange, interpreting time series data, and even exploring chess
puzzles. Along the way, you'll learn to easily transfer existing
data pipelines to Julia. What's inside Read and write data in
various formats Work with tabular data, including subsetting,
grouping, and transforming Create data processing pipelines Create
web services sharing results of data analysis Write readable and
efficient Julia programs About the reader For data scientists
familiar with Python or R. No experience with Julia required. About
the author Bogumil Kaminski iis one of the lead developers of
DataFrames.jl--the core package for data manipulation in the Julia
ecosystem. He has over 20 years of experience delivering data
science projects. Table of Contents 1 Introduction PART 1 ESSENTIAL
JULIA SKILLS 2 Getting started with Julia 3 Julia's support for
scaling projects 4 Working with collections in Julia 5 Advanced
topics on handling collections 6 Working with strings 7 Handling
time-series data and missing values PART 2 TOOLBOX FOR DATA
ANALYSIS 8 First steps with data frames 9 Getting data from a data
frame 10 Creating data frame objects 11 Converting and grouping
data frames 12 Mutating and transforming data frames 13 Advanced
transformations of data frames 14 Creating web services for sharing
data analysis results
General
Imprint: |
Manning Publications
|
Country of origin: |
United States |
Release date: |
2023 |
First published: |
2023 |
Authors: |
Bogumil Kaminski
|
Dimensions: |
235 x 185 x 22mm (L x W x T) |
Format: |
Paperback
|
Pages: |
426 |
ISBN-13: |
978-1-63343-936-8 |
Categories: |
Books >
Computing & IT >
Computer programming >
General
|
LSN: |
1-63343-936-4 |
Barcode: |
9781633439368 |
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