Dplyr | r programming for data analysis
Dplyr is part of Tidyverse package from in r programming for data analysis and data manipulation ,exploratory data analysis. Exploratory data wrangling is made very easy with dplyr in r.
git link : https://github.com/coders-digest/R-Pr...
0:00 Dplyr Introduction
2:16 Basic Dplyr functions
6:55 Arrange function in dplyr
8:30 case verb
12:46 filter function in dplyr
15:34 %in% operator dplyr
16:12 elect and select if function
18:39 group by in dplyr
21:22 count function
22:41 distinct and n_distinct
23:57 mutate in dplyr
25:35 if else in dplyr
27:53 summarise and summarise each
34:01 joins in dplyr
Data wrangling is often the most time-consuming part of data science and applied statistics.
Tabular data is data regardless of where it lives, so you should use the same functions to work with it. With dplyr, anything you can do to a local data frame you can also do to a remote database table. PostgreSQL, MySQL, SQLite and Google bigquery support is built-in; adding a new backend is a matter of implementing a handful of S3 methods.
and so it makes dplyr an extremely fast and powerful tool for data analysis , data mining and data exploration.