Animated Plot
Deepansha Adlakha
3/2/2023
Packages
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install.packages(c('gapminder','ggplot2','gganimate','gifski','tidyverse'),repos="https://cran.us.r-project.org")## Installing packages into 'C:/Users/Dell/Documents/R/win-library/4.1'
## (as 'lib' is unspecified)## package 'gapminder' successfully unpacked and MD5 sums checked
## package 'ggplot2' successfully unpacked and MD5 sums checked
## package 'gganimate' successfully unpacked and MD5 sums checked
## package 'gifski' successfully unpacked and MD5 sums checked
## package 'tidyverse' successfully unpacked and MD5 sums checked
##
## The downloaded binary packages are in
## C:\Users\Dell\AppData\Local\Temp\RtmpK4QaAd\downloaded_packageslibrary(gapminder)## Warning: package 'gapminder' was built under R version 4.1.3library(ggplot2)## Warning: package 'ggplot2' was built under R version 4.1.3library(gganimate)## Warning: package 'gganimate' was built under R version 4.1.3library(gifski)## Warning: package 'gifski' was built under R version 4.1.3library(tidyverse)## Warning: package 'tidyverse' was built under R version 4.1.3## Warning: package 'tibble' was built under R version 4.1.3## Warning: package 'tidyr' was built under R version 4.1.3## Warning: package 'readr' was built under R version 4.1.3## Warning: package 'purrr' was built under R version 4.1.3## Warning: package 'dplyr' was built under R version 4.1.3## Warning: package 'stringr' was built under R version 4.1.3## Warning: package 'forcats' was built under R version 4.1.3## Warning: package 'lubridate' was built under R version 4.1.3## -- Attaching core tidyverse packages ------------------------ tidyverse 2.0.0 --
## v dplyr 1.1.0 v readr 2.1.4
## v forcats 1.0.0 v stringr 1.5.0
## v lubridate 1.9.2 v tibble 3.1.8
## v purrr 1.0.1 v tidyr 1.3.0## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
## i Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorsavocado <- read_csv("avocado.csv")## New names:
## Rows: 18249 Columns: 14
## -- Column specification
## -------------------------------------------------------- Delimiter: "," chr
## (2): type, region dbl (11): ...1, AveragePrice, Total Volume, 4046, 4225, 4770,
## Total Bags, S... date (1): Date
## i Use `spec()` to retrieve the full column specification for this data. i
## Specify the column types or set `show_col_types = FALSE` to quiet this message.
## * `` -> `...1`summary(avocado)## ...1 Date AveragePrice Total Volume
## Min. : 0.00 Min. :2015-01-04 Min. :0.440 Min. : 85
## 1st Qu.:10.00 1st Qu.:2015-10-25 1st Qu.:1.100 1st Qu.: 10839
## Median :24.00 Median :2016-08-14 Median :1.370 Median : 107377
## Mean :24.23 Mean :2016-08-13 Mean :1.406 Mean : 850644
## 3rd Qu.:38.00 3rd Qu.:2017-06-04 3rd Qu.:1.660 3rd Qu.: 432962
## Max. :52.00 Max. :2018-03-25 Max. :3.250 Max. :62505647
## 4046 4225 4770 Total Bags
## Min. : 0 Min. : 0 Min. : 0 Min. : 0
## 1st Qu.: 854 1st Qu.: 3009 1st Qu.: 0 1st Qu.: 5089
## Median : 8645 Median : 29061 Median : 185 Median : 39744
## Mean : 293008 Mean : 295155 Mean : 22840 Mean : 239639
## 3rd Qu.: 111020 3rd Qu.: 150207 3rd Qu.: 6243 3rd Qu.: 110783
## Max. :22743616 Max. :20470573 Max. :2546439 Max. :19373134
## Small Bags Large Bags XLarge Bags type
## Min. : 0 Min. : 0 Min. : 0.0 Length:18249
## 1st Qu.: 2849 1st Qu.: 127 1st Qu.: 0.0 Class :character
## Median : 26363 Median : 2648 Median : 0.0 Mode :character
## Mean : 182195 Mean : 54338 Mean : 3106.4
## 3rd Qu.: 83338 3rd Qu.: 22029 3rd Qu.: 132.5
## Max. :13384587 Max. :5719097 Max. :551693.7
## year region
## Min. :2015 Length:18249
## 1st Qu.:2015 Class :character
## Median :2016 Mode :character
## Mean :2016
## 3rd Qu.:2017
## Max. :2018class(avocado$Date)## [1] "Date"unique(avocado$region)## [1] "Albany" "Atlanta" "BaltimoreWashington"
## [4] "Boise" "Boston" "BuffaloRochester"
## [7] "California" "Charlotte" "Chicago"
## [10] "CincinnatiDayton" "Columbus" "DallasFtWorth"
## [13] "Denver" "Detroit" "GrandRapids"
## [16] "GreatLakes" "HarrisburgScranton" "HartfordSpringfield"
## [19] "Houston" "Indianapolis" "Jacksonville"
## [22] "LasVegas" "LosAngeles" "Louisville"
## [25] "MiamiFtLauderdale" "Midsouth" "Nashville"
## [28] "NewOrleansMobile" "NewYork" "Northeast"
## [31] "NorthernNewEngland" "Orlando" "Philadelphia"
## [34] "PhoenixTucson" "Pittsburgh" "Plains"
## [37] "Portland" "RaleighGreensboro" "RichmondNorfolk"
## [40] "Roanoke" "Sacramento" "SanDiego"
## [43] "SanFrancisco" "Seattle" "SouthCarolina"
## [46] "SouthCentral" "Southeast" "Spokane"
## [49] "StLouis" "Syracuse" "Tampa"
## [52] "TotalUS" "West" "WestTexNewMexico"avocado_us <- avocado %>% filter(region == "TotalUS")
states <- c("California")
avocado_CA <- avocado %>% filter(region %in% states)
regions <- c("West","Southeast","SouthCentral","Plains","Northeast","Midsouth","GreatLakes","WestTexNewMexico","NorthernNewEngland")
avocado_region <- avocado %>% filter(region %in% regions)
avocado_cities <- avocado %>% filter(!region %in% c("TotalUS", states, regions))
ggplot(data = avocado_us,
mapping = aes(x = Date, y = AveragePrice, color = type)) +
geom_line() +
scale_y_continuous(labels = scales::dollar_format()) +
scale_color_manual(values= c("red1", "red4")) +
theme_minimal() +
labs(title = "Average Price of US Avocados",
caption = "Source: Kaggle") + transition_reveal(Date)+theme(
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="#333333", size=14, face="bold"),
axis.title.y = element_text(color="#333333", size=14, face="bold")
)## `geom_line()`: Each group consists of only one observation.
## i Do you need to adjust the group aesthetic?
## `geom_line()`: Each group consists of only one observation.
## i Do you need to adjust the group aesthetic?