Data manipulation in R

DPLYR Package Basics

Dplyr is a very powerful package for data manipulation in R. The 6 main verbs for dplyr are -
1. Select
2. Filter
3. Arrange
4. Group
5. Mutate
6. Summarise

Together, these verbs can be used to perform powerful data analysis.

Select

All you need to know about select function.

#Shown below are 2 ways to select the set of columns. Notice, how easy it becomes when we make use of the select function. The "%>%" is the piping operator and is of great use when longer codes need to be written.

> #Difficult way
> hflights[c("Year","Month","DayOfWeek","DepTime","ArrTime")]
Source: local data frame [227,496 x 5]
 
   Year Month DayOfWeek DepTime ArrTime
1  2011     1         6    1400    1500
2  2011     1         7    1401    1501
3  2011     1         1    1352    1502
4  2011     1         2    1403    1513
5  2011     1         3    1405    1507
6  2011     1         4    1359    1503
7  2011     1         5    1359    1509
8  2011     1         6    1355    1454
9  2011     1         7    1443    1554
10 2011     1         1    1443    1553
..  ...   ...       ...     ...     ...
> #Easy Way
> hflights %>%
          select(Year:ArrTime, - DayofMonth)

Mutate

Mutate is used to create new columns. You can always reuse variables created within mutate function to create more columns. Always remember that the new columns are created to a copy of the dataset.
Let's write a code to create 2 new columns - TotalTaxiTime, GroundTime

#Creating new columns
hflights %>%
          mutate(TotalTaxiTime = TaxiIn+ TaxiOut, GroundTime = ActualElapsedTime - ArrTime)