Data Wrangling with R

by Bradley C. Boehmke

1. Preface 2. Introduction a. The Role of Data Wrangling i. Introduction to R 1. Open Source 2. Flexibility 3. Community ii. R Basics 1. Assignment & Evaluation 2. Vectorization 3. Getting help 4. Workspace 5. Working with packages 6. Style guide
3. Working with Different Types of Data in R a. Dealing with Numbers i. Integer vs. Double ii. Generating sequence of non-random numbers iii. Generating sequence of random numbers iv. Setting the seed for reproducible random numbers v. Comparing numeric values vi. Rounding numbers b. Dealing with Character Strings i. Character string basics ii. String manipulation with base R iii. String manipulation with stringr iv. Set operatons for character strings c. Dealing with Regular Expressions i. Regex Syntax ii. Regex Functions iii. Additional resources d. Dealing with Factors i. Creating, converting & inspecting factors ii. Ordering levels iii. Revalue levels iv. Dropping levels e. Dealing with Dates i. Getting current date & time ii. Converting strings to dates iii. Extract & manipulate parts of dates iv. Creating date sequences v. Calculations with dates vi. Dealing with time zones & daylight savings vii. Additional resources
<4. Managing Data Structures in R a. Data Structure Basics i. Identifying the Structure ii. Attributes b. Managing Vectors i. Creating ii. Adding on to iii. Adding attributes iv. Subsetting c. Managing Lists i. Creating iii. Adding attributes iv. Subsetting d. Managing Matrices i. Creating ii. Adding on to iii. Adding attributes iv. Subsetting e. Managing Data Frames i. Creating ii. Adding on to iii. Adding attributes iv. Subsetting f. Dealing with Missing Values i. Testing for missing values ii. Recoding missing values iii. Excluding missing values
5. Importing, Scraping, and Exporting Data with R a. Importing Data i. Reading data from text files ii. Reading data from Excel files iii. Load data from saved R object file iv. Additional resources b. Scraping Data i. Importing tabular and Excel files stored online ii. Scraping HTML text iii. Scraping HTML table data iv. Working with APIs v. Additional Resources c. Exporting Data i. Writing data to text files ii. Writing data to Excel files iii. Saving data as an R object file iv. Additional resources
6. Creating Efficient & Readable Code in R a. Functions i. Function Components i

Kindle Edition

Published February 27, 2016

Reviews

[ریچارد · Rating 5 out of 5]

بیشتر شبیه رفرنسیه که مطمئن باشی مقدمات کارها رو بلدی، و احیانا چیزی جا نمونده باشه از دستورها. برای یادگیری خیلی خوب نیست، خیلی مثال نداره ولی توضیحاتش واضحه

[Kier O'Neil · Rating 4 out of 5]

Great book that focuses on things that R programmers really do, like using the dplyr package instead of base R for dataframe manipulation.
Well written with great examples.
I recommend a longer version in the future that takes a deeper dive.

[Mills College Library]

519.535 B6714 2016