dplyr: Getting Started
38The is the first video in a tutorial series covering the basics of the dplyr library in R for data manipulation and cleaning.
I learned many of the practical coding skills used to make my videos taking courses on DataCamp:
► https://www.datacamp.com?tap_a=5644-dce66f&tap_s=777784-8ccc64&utm_medium=affiliate&utm_source=gregoryhamel
The dplyr package is a data manipulation library for R that provides a variety of helpful functions for doing common data cleaning tasks. dplyr lets you subset, reshape, join and summarize data, typically using less code than would be required in base R and with syntax that is often easier to read and logic that is easier to follow.
Dplyr is a part of the R tidyverse: an ecosystem of several libraries designed to work together by representing data in common formats. To load the dplyr library, you can install and load it as a standalone package or load the tidyverse. In addition to dplyr, the tidyverse includes ggplot2 for data visualization, stringr for string manipulation, reader for data importing, tibble which extends data frame objects with additional functionality and a few other packages.
View the whole dplyr in R playlist here:
https://www.youtube.com/watch?v=THGFXV4RW8U&list=PLiC1doDIe9rC8RgWPAWqDETE-VbKOWfWl
Link to the Kaggle Notebook code used for this video series:
https://www.kaggle.com/hamelg/dplyr-in-r
dplyr cheat sheet from RStudio:
https://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf
dplyr documentation:
https://cran.r-project.org/web/packages/dplyr/dplyr.pdf
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Other Videos By DataDaft
| 2019-10-06 | dplyr: Grouping |
| 2019-10-05 | dplyr: summarize |
| 2019-10-03 | MLB All-Time Team Records: Most Home Runs Hit in a Season (1871-2019) |
| 2019-09-30 | dplyr: gather and spread |
| 2019-09-28 | dplyr: separate and unite |
| 2019-09-27 | dplyr: mutate |
| 2019-09-25 | dlpyr: rename and arrange |
| 2019-09-24 | dplyr: select |
| 2019-09-17 | dplyr: filter |
| 2019-09-13 | dplyr: Pipes |
| 2019-09-13 | dplyr: Getting Started |
| 2019-09-11 | Introduction to R: Descriptive Statistics |
| 2019-09-06 | How to Read csv Data Into R |
| 2019-09-05 | Introduction to R: Plotting with ggplot2 |
| 2019-09-04 | How To Use ifelse in R |
| 2019-09-03 | Introduction to R: Plotting in Base R |
| 2019-08-28 | Introduction to R: Frequency Tables |
| 2019-08-27 | Introduction to R: Merging Data |
| 2019-08-23 | Introduction to R: Dealing With Dates |
| 2019-08-21 | Introduction to R: Preparing Numeric Data |
| 2019-08-20 | Introduction to R: Working with Text Data |