How To Use Comparison Operators In R

Introduction

In this article I am going to demonstrate how to use comparison operators in R to filter the data of a particular dataset accordingly. To demonstrate the use of comparison operators we will be using dplyr package along with planes dataset in R. We will be using filter function provided with the dplyr package to manipulate and transform the data and to create subset of data as well.

Loading package and dataset

We will be using predefined planes dataset which belongs to package named nycflights13. Therefore we need to load the package first as follows,

library(nycflights13)

Now we need to load the dataset planes as we will be using planes dataset to filter the data.

> planes

To use the filter function, we need to load the library named dplyr. We can use below syntax to load dplyr library,

> planes
# A tibble: 3,322 x 9
tailnum year type manufacturer model engines seats speed engine
<chr> <int> <chr> <chr> <chr> <int> <int> <int> <chr>
1 N10156 2004 Fixed wing multi engine EMBRAER EMB-145XR 2 55 NA Turbo-fan
2 N102UW 1998 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
3 N103US 1999 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
4 N104UW 1999 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
5 N10575 2002 Fixed wing multi engine EMBRAER EMB-145LR 2 55 NA Turbo-fan
6 N105UW 1999 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
7 N107US 1999 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
8 N108UW 1999 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
9 N109UW 1999 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
10 N110UW 1999 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
# ... with 3,312 more rows

Using filter function

> library(dplyr)
Attaching package: ‘dplyr’
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, union
>

Different comparison operators

We can use filter function with different kinds of comparison operators to filter the dataset and to create a subset of data displaying data on the basis of conditions including comparison operators. R contains various comparison operators such as >, >=, <, <=.

Greater than operator

Using greater than operator, we can display values which are greater than the value specified in the filter function.

Let us discuss this operator with the help of example below,

> filter(planes, year > 1999, seats > 55)
# A tibble: 1,606 x 9
tailnum year type manufacturer model engines seats speed engine
<chr> <int> <chr> <chr> <chr> <int> <int> <int> <chr>
1 N11206 2000 Fixed wing multi engine BOEING 737-824 2 149 NA Turbo-fan
2 N117UW 2000 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
3 N118US 2000 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
4 N119US 2000 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
5 N121UW 2000 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
6 N122US 2000 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
7 N123UW 2000 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
8 N124US 2000 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
9 N125UW 2009 Fixed wing multi engine AIRBUS A320-214 2 182 NA Turbo-fan
10 N126UW 2009 Fixed wing multi engine AIRBUS A320-214 2 182 NA Turbo-fan
# ... with 1,596 more rows

In the argument part of the filter function, we have mentioned year > 1999 and seat > 55, therefore a new dataset containing all the observations of year greater than 1999 and all the observations of seat greater than 55 will be displayed.

Less than operator

Using less than operator, we can display values which are less than the value specified in the filter function.

Let us discuss this operator with the help of example below,

> filter(planes, year < 1999, seats < 55)
# A tibble: 28 x 9
tailnum year type manufacturer model engines seats speed engine
<chr> <int> <chr> <chr> <chr> <int> <int> <int> <chr>
1 N201AA 1959 Fixed wing single engine CESSNA 150 1 2 90 Reciprocating
2 N202AA 1980 Fixed wing multi engine CESSNA 421C 2 8 90 Reciprocating
3 N344AA 1992 Fixed wing multi engine GULFSTREAM AEROSPACE G-IV 2 22 NA Turbo-fan
4 N347AA 1985 Rotorcraft SIKORSKY S-76A 2 14 NA Turbo-shaft
5 N350AA 1980 Fixed wing multi engine PIPER PA-31-350 2 8 162 Reciprocating
6 N364AA 1973 Fixed wing multi engine CESSNA 310Q 2 6 167 Reciprocating
7 N376AA 1978 Fixed wing single engine PIPER PA-32RT-300 1 7 NA Reciprocating
8 N378AA 1963 Fixed wing single engine CESSNA 172E 1 4 105 Reciprocating
9 N383AA 1972 Fixed wing multi engine BEECH E-90 2 10 NA Turbo-prop
10 N393AA 1994 Rotorcraft BELL 230 2 11 NA Turbo-shaft
# ... with 18 more rows

In the argument part of the filter function, we have mentioned year < 1999 and seat < 55, therefore a new dataset containing all the observations of years less than 1999 and all the observations of seat less than 55 will be displayed.

Greater than or equal to operator

Using greater than or equal to operator, we can display values which are either greater than or equal to the value specified in the filter function.

Let us discuss this operator with the help of the example below,

> filter(planes, year >= 1999, seats >= 55)
# A tibble: 2,148 x 9
tailnum year type manufacturer model engines seats speed engine
<chr> <int> <chr> <chr> <chr> <int> <int> <int> <chr>
1 N10156 2004 Fixed wing multi engine EMBRAER EMB-145XR 2 55 NA Turbo-fan
2 N103US 1999 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
3 N104UW 1999 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
4 N10575 2002 Fixed wing multi engine EMBRAER EMB-145LR 2 55 NA Turbo-fan
5 N105UW 1999 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
6 N107US 1999 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
7 N108UW 1999 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
8 N109UW 1999 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
9 N110UW 1999 Fixed wing multi engine AIRBUS INDUSTRIE A320-214 2 182 NA Turbo-fan
10 N11106 2002 Fixed wing multi engine EMBRAER EMB-145XR 2 55 NA Turbo-fan
# ... with 2,138 more rows
>

In the argument part of the filter function, we have mentioned year >= 1999 and seat >= 55, therefore a new dataset containing all the observations of year greater than or equal to 1999 and all the observations of seat greater than or equal to 55 will be displayed.

Less than or equal to operator

Using less than or equal to operator, we can display values which are either less than or equal to the value specified in the filter function.

Let us discuss this operator with the help of the example below,

> filter(planes, year <= 1999, seats <= 55)
# A tibble: 76 x 9
tailnum year type manufacturer model engines seats speed engine
<chr> <int> <chr> <chr> <chr> <int> <int> <int> <chr>
1 N12957 1998 Fixed wing multi engine EMBRAER EMB-145LR 2 55 NA Turbo-fan
2 N12967 1999 Fixed wing multi engine EMBRAER EMB-145LR 2 55 NA Turbo-fan
3 N13949 1998 Fixed wing multi engine EMBRAER EMB-145LR 2 55 NA Turbo-fan
4 N13955 1998 Fixed wing multi engine EMBRAER EMB-145LR 2 55 NA Turbo-fan
5 N13956 1998 Fixed wing multi engine EMBRAER EMB-145LR 2 55 NA Turbo-fan
6 N13958 1998 Fixed wing multi engine EMBRAER EMB-145LR 2 55 NA Turbo-fan
7 N13964 1999 Fixed wing multi engine EMBRAER EMB-145LR 2 55 NA Turbo-fan
8 N13965 1999 Fixed wing multi engine EMBRAER EMB-145LR 2 55 NA Turbo-fan
9 N13968 1999 Fixed wing multi engine EMBRAER EMB-145LR 2 55 NA Turbo-fan
10 N13969 1999 Fixed wing multi engine EMBRAER EMB-145LR 2 55 NA Turbo-fan
# ... with 66 more rows

In the argument part of the filter function, we have mentioned year <= 1999 and seat <= 55, therefore a new dataset containing all the observations of year less than or equal to 1999 and all the observations of seat less than or equal to 55 will be displayed.

Conclusion

In this article I demonstrated how to use comparison operators in R to filter the data of a particular dataset accordingly. To demonstrate the use of comparison operators, dplyr package along with planes dataset in R is used. Filter function which is provided with dplyr package to filter the data is also used.