Using dplyr for data visulization (Part1: FILTER)

###Using package dplyr for data visualization###

rm(list=ls())

options(repos = c(CRAN = "http://cran.rstudio.com"))

install.packages("nycflights13")

library(nycflights13)

library(tidyverse)

###Using flights data to practice###

int stands for integers.

dbl stands for doubles, or real numbers.

chr stands for character vectors, or strings.

dttm stands for date-times (a date + a time)

lgl stands for logical, vectors that contain only TRUE or FALSE

fctr stands for factors, which R uses to represent categorical variables with fixed possible values

date stands for dates

?flights

nycflights13::flights

head(flights, n= 10)

### Using dplyr function to manipulate the data ###

Filter (): Pick observations by their values

Arrange (): Reorder the rows

Select (): Pick variables by their names

Mutate(): Create new variables with functions of existing variables

Summarize (): Collapse many values down to a single summary

Group_by():changes the scope of each function from operating on the entire dataset to operating on it group-by-group

Filter:

filter(flights, month == 1, day == 1)

filter(flights, month == 2, day == 2)

jan1 <- filter(flights, month ==1, day ==1)

head(jan1, n =10)

dec25 <- filter(flights, month == 12, day ==25)

head(dec25, n =9)

### Comparision: the standard suite: >, >=, <, <=, != (not equal), and == (equal)###

###Boolean operators: & is “and,” | is “or,” and ! is “not.”

filter(flights, month == 11 | month ==12)

### x %in% y: This will select every row where x is one of the values in y

nov_dec <- filter(flights, month %in% c(11,12))

### find flights that weren’t delayed (on arrival or departure) by more than two hours

filter(flights, !(arr_delay >=120 | dep_delay >=120))

filter(flights, !(arr_delay >= 45 & dep_delay >=45))

filter(flights, (arr_delay <=-3 | dep_delay <=-3 ))