(R Tutorials for Business Analyst)
R Data Frame Sorting using Order()
In data analysis you can sort your data according to a certain variable in the dataset. In R, we can use the help of the function order(). In R, we can easily sort a vector of continuous variable or factor variable. Arranging the data can be of ascending or descending order.
Syntax:
sort(x, decreasing = FALSE, na.last = TRUE):
Argument:
- x: A vector containing continuous or factor variable
- decreasing: Control for the order of the sort method. By default, decreasing is set to `FALSE`.
- last: Indicates whether the `NA` ‘s value should be put last or not
Example 1
For instance, we can create a tibble data frame and sort one or multiple variables. A tibble data frame is a new approach to data frame. It improves the syntax of data frame and avoid frustrating data type formatting, especially for character to factor. It is also a convenient way to create a data frame by hand, which is our purpose here. To learn more about tibble, please refer to the vignette: https://cran.r-project.org/web/packages/tibble/vignettes/tibble.html
library(dplyr) set.seed(1234) data_frame <- tibble( c1 = rnorm(50, 5, 1.5), c2 = rnorm(50, 5, 1.5), c3 = rnorm(50, 5, 1.5), c4 = rnorm(50, 5, 1.5), c5 = rnorm(50, 5, 1.5) ) # Sort by c1 df <-data_frame[order(data_frame$c1),] head(df)
Output:
# A tibble: 6 x 5 ## c1 c2 c3 c4 c5 ## <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 1.481453 3.477557 4.246283 3.686611 6.0511003 ## 2 1.729941 5.824996 4.525823 6.753663 0.1502718 ## 3 2.556360 6.275348 2.524849 6.368483 5.4787404 ## 4 2.827693 4.769902 5.120089 3.743626 4.0103449 ## 5 2.988510 4.395902 2.077631 4.236894 4.6176880 ## 6 3.122021 6.317305 5.413840 3.551145 5.6067027
Example 2
# Sort by c3 and c4 df <-data_frame[order(data_frame$c3, data_frame$c4),] head(df)
Output:
# A tibble: 6 x 5 ## c1 c2 c3 c4 c5 ## <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 2.988510 4.395902 2.077631 4.236894 4.617688 ## 2 2.556360 6.275348 2.524849 6.368483 5.478740 ## 3 3.464516 3.914627 2.730068 9.565649 6.016123 ## 4 4.233486 3.292088 3.133568 7.517309 4.772395 ## 5 3.935840 2.941547 3.242078 6.464048 3.599745 ## 6 3.835619 4.947859 3.335349 4.378370 7.240240
Example 3
# Sort by c3(descending) and c4(acending) df <-data_frame[order(-data_frame$c3, data_frame$c4),] head(df)
Output:
# A tibble: 6 x 5 ## c1 c2 c3 c4 c5 ## <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 4.339178 4.450214 8.087243 4.5010140 8.410225 ## 2 3.959420 8.105406 7.736312 7.1168936 5.431565 ## 3 3.339023 3.298088 7.494285 5.9303153 7.035912 ## 4 3.397036 5.382794 7.092722 0.7163620 5.620098 ## 5 6.653446 4.733315 6.520536 0.9016707 4.513410 ## 6 4.558559 4.712609 6.380086 6.0562703 5.044277
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