Command Line Data Analysis

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Miki Tebeka

58:13

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01 - Introduction

01 - Command-line data analysis.mp4

00:25

02 - What you should know.mp4

00:20

03 - Setting up.mp4

00:36

02 - 1. The Command Line

01 - The shell.mp4

01:53

02 - Running programs.mp4

02:03

03 - Shell expansion.mp4

01:17

04 - Pipes and redirects.mp4

02:49

05 - Files and directories.mp4

02:51

06 - Installing commands.mp4

01:26

03 - 2. Data Ingestion

01 - Cat and less.mp4

01:56

02 - curl.mp4

02:11

03 - SCP.mp4

01:44

04 - gsutil and AWS CLI.mp4

02:28

05 - Databases.mp4

01:08

06 - Challenge ETL.mp4

01:04

07 - Solution ETL.mp4

01:28

04 - 3. Selecting Data

01 - head, tail, and shuf.mp4

01:56

02 - grep and regular expressions.mp4

01:28

03 - cut.mp4

00:59

04 - jq.mp4

01:17

05 - Databases.mp4

02:36

06 - Challenge Station status.mp4

00:34

07 - Solution Station status.mp4

00:49

05 - 4. Data Transformations

01 - tr.mp4

01:12

02 - sed.mp4

02:05

03 - AWK.mp4

01:11

04 - Challenge Normalized items.mp4

00:21

05 - Solution Normalized items.mp4

00:45

06 - 5. Calculations

01 - sort and uniq.mp4

02:00

02 - bc.mp4

01:59

03 - AWK.mp4

00:51

04 - Challenge Quantity sold.mp4

00:16

05 - Solution Quantity sold.mp4

00:51

07 - 6. Visualization

01 - printf.mp4

01:27

02 - gnuplot Introduction.mp4

00:53

03 - gnuplot Box plots.mp4

03:50

04 - gnuplot Bar charts.mp4

02:21

05 - Challenge Weather.mp4

00:35

06 - Solution Weather.mp4

01:42

08 - Conclusion

01 - Next steps.mp4

00:36

Description

In this course, Miki Tebeka presents the information and instructions you need to perform data analysis using the many tools that the command line offers for quick data analysis and visualization. Learn how to use the command line and command line tools for analyzing and displaying data. Go over Unix shell basics, and then use tools like grep, jq, sed, awk, curl, gnuplot, and others to analyze and display data from various sources, such as CSV files, APIs, databases, and more.

This course is integrated with GitHub Codespaces, an instant cloud developer environment that offers all the functionality of your favorite IDE without the need for any local machine setup. With GitHub Codespaces, you can get hands-on practice from any machine, at any time—all while using a tool that you’ll likely encounter in the workplace.

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Data Science

Data Analysis

Miki Tebeka

Instructor's Courses

Teaching effective hands-on workshops all of the world. Consultant solving hard problem with the right tools (Java and C++ are *not* the right tools ;). Book author, LinkedIn learning Author, open source contributor and convention organizer, meetup co host and coding for fun in my spare time. Specialties: Python & Scientific Python (Expert), Go (Expert), C/C++, Clojure, JavaScript, bash, ... Information retrieval - tokenization, summarization, clustering, search ... Concurrency - Multi process, multi threaded, Hadoop ... Web development - REST APIs, jQuery, JavaScript, CSS, (X)HTML Assemblers, Linkers, Debugger, Simulators SCM tools (git, Mercurial, Perforce, subversion, CVS, ClearCase) Linux, OS X and Windows Functional Programming, OOD, OOP Databases - SQL (BigQuery, PostgreSQL, MySQL, Oracle) and NoSQL (Redis, MongoDB, CouchDB)

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