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Hands-On Data Science with the Command Line : Automate Everyday Data Science Tasks Using Command-Line Tools.

By: Contributor(s): Material type: TextTextPublication details: Birmingham : Packt Publishing Ltd, 2019.Description: 1 online resource (121 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781788991919
  • 1788991915
Subject(s): Genre/Form: Additional physical formats: Print version:: Hands-On Data Science with the Command Line : Automate Everyday Data Science Tasks Using Command-Line Tools.DDC classification:
  • 005.7565 23
LOC classification:
  • QA76.9.D3
Online resources:
Contents:
Cover; Title Page; Copyright and Credits; About Packt; Contributors; Table of Contents; Preface; Chapter 1: Data Science at the Command Line and Setting It Up; History of the command line; We don't want to BaSH other shells, but ... ; Language-focused shells; So, why the command line?; Getting set up with Windows 10; Getting set up on OS X; Getting set up on Ubuntu Linux; Getting set up with Docker; Summary; Chapter 2: Essential Commands; Essential commands; Navigating the command line; Getting help; Customizing the shell; Summary; Chapter 3: Shell Workflows, and Data Acquisition and Massaging
Download the dataUsing the file command; Performing a word count; Introduction to cut; Detached processing; How to background a process; Disregarding SIGHUP; Terminal multiplexers; Introduction to screen; Sharing a screen session between multiple users; Introduction to tmux; Summary; Chapter 4: Bash Functions and Data Visualization; My first shell script; She bangs, she bangs!; Function arguments, positional parameters, and IFS; Prompt me baby one more time; Feed the function input!; Down the rabbit hole of IFS and bash arrays; Advanced shell scripting magic; Here be dragons, ye be warned
Text injection of text filesBash networks for fun and profit!; From dumb Terminal to glam Terminal; Who, what, where, why, how?; Enter the mind's eye; Summary; Chapter 5: Loops, Functions, and String Processing; Once, twice, three times a lady loops; It's the end of the world as we know it while and until ; The simple case; Pay no heed to the magician redirecting your attention; Regular expressions and grep; Exact matches; Character sets; Dot the i (or anything else); Capture groups; Either or, neither nor; Repetition; Other operators; Putting it all together; awk, sed, and tr; awk; sed; tr
Sort and uniq sort; uniq; Summary; Chapter 6: SQL, Math, and Wrapping it up; cut and viewing data as columnar; WHERE clauses; Join, for joining data; Group by and ordering; Simulating selects; Keys to the kingdom; Using SQLite; Math in bash itself; Using let; Basic arithmetic; Double-parentheses; bc, the unix basic calculator; Math in (g)awk; Python (pandas, numpy, scikit-learn); Analyzing weather data in bash; Summary; Other Books You May Enjoy; Index
Summary: The science of gathering and extracting information from data-intensive applications bring in the challenge of writing complex libraries and efficient programs using high level languages like Python, R, so on. This book aims to explore the power of ""Unix-styled"" scripting tools like awk, bash, grep and package them as highly efficient built-in ...
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Print version record.

Cover; Title Page; Copyright and Credits; About Packt; Contributors; Table of Contents; Preface; Chapter 1: Data Science at the Command Line and Setting It Up; History of the command line; We don't want to BaSH other shells, but ... ; Language-focused shells; So, why the command line?; Getting set up with Windows 10; Getting set up on OS X; Getting set up on Ubuntu Linux; Getting set up with Docker; Summary; Chapter 2: Essential Commands; Essential commands; Navigating the command line; Getting help; Customizing the shell; Summary; Chapter 3: Shell Workflows, and Data Acquisition and Massaging

Download the dataUsing the file command; Performing a word count; Introduction to cut; Detached processing; How to background a process; Disregarding SIGHUP; Terminal multiplexers; Introduction to screen; Sharing a screen session between multiple users; Introduction to tmux; Summary; Chapter 4: Bash Functions and Data Visualization; My first shell script; She bangs, she bangs!; Function arguments, positional parameters, and IFS; Prompt me baby one more time; Feed the function input!; Down the rabbit hole of IFS and bash arrays; Advanced shell scripting magic; Here be dragons, ye be warned

Text injection of text filesBash networks for fun and profit!; From dumb Terminal to glam Terminal; Who, what, where, why, how?; Enter the mind's eye; Summary; Chapter 5: Loops, Functions, and String Processing; Once, twice, three times a lady loops; It's the end of the world as we know it while and until ; The simple case; Pay no heed to the magician redirecting your attention; Regular expressions and grep; Exact matches; Character sets; Dot the i (or anything else); Capture groups; Either or, neither nor; Repetition; Other operators; Putting it all together; awk, sed, and tr; awk; sed; tr

Sort and uniq sort; uniq; Summary; Chapter 6: SQL, Math, and Wrapping it up; cut and viewing data as columnar; WHERE clauses; Join, for joining data; Group by and ordering; Simulating selects; Keys to the kingdom; Using SQLite; Math in bash itself; Using let; Basic arithmetic; Double-parentheses; bc, the unix basic calculator; Math in (g)awk; Python (pandas, numpy, scikit-learn); Analyzing weather data in bash; Summary; Other Books You May Enjoy; Index

The science of gathering and extracting information from data-intensive applications bring in the challenge of writing complex libraries and efficient programs using high level languages like Python, R, so on. This book aims to explore the power of ""Unix-styled"" scripting tools like awk, bash, grep and package them as highly efficient built-in ...

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