gglot showing wrong state data

[twwzx]

I am really new to R and learning the ggplot.

First, I pulled the map of united state using map_data function with the "state" dataset
Next, I merged my impression data broken down by states with the "states" data to get the impression by state.
Last, I used gglot to show the map and fill with the impression data.
However, the final plot shown as the screenshot below is not quite right.

the AEP data I used below is simple as below:

data.frame(Impressions = c(9434L, 10060L, 5686L, 22694L, 5998L), 
    region = as.factor(c("alabama", "arizona", "arkansas", "california", 
        "colorado")))
#>   Impressions     region
#> 1        9434    alabama
#> 2       10060    arizona
#> 3        5686   arkansas
#> 4       22694 california
#> 5        5998   colorado

^{Created on 2019-10-08 by the reprex package (v0.3.0)}

library(tidyverse)
library(ggmap)

states <- map_data("state")
head(states)

AEP <- read.csv("C:/Users/czhao01/Documents/Humana-AEP.csv")
head(AEP)

mapdata <- merge(states, AEP, by="region") (I pasted the sample merged data below)

data.frame(stringsAsFactors = FALSE, region = c("alabama", "alabama", 
    "alabama", "alabama", "alabama"), long = c(-87.53076171875, 
    -87.4849319458008, -87.8172378540039, -87.5708694458008, 
    -87.525032043457), lat = c(30.3323860168457, 30.3724918365479, 
    30.3438453674316, 30.3266544342041, 30.3724918365479), group = c(1, 
    1, 1, 1, 1), order = c(4L, 2L, 23L, 5L, 3L), subregion = c(NA, 
    NA, NA, NA, NA), Impressions = c(9434L, 9434L, 9434L, 9434L, 
    9434L))
#>    region      long      lat group order subregion Impressions
#> 1 alabama -87.53076 30.33239     1     4        NA        9434
#> 2 alabama -87.48493 30.37249     1     2        NA        9434
#> 3 alabama -87.81724 30.34385     1    23        NA        9434
#> 4 alabama -87.57087 30.32665     1     5        NA        9434
#> 5 alabama -87.52503 30.37249     1     3        NA        9434

^{Created on 2019-10-08 by the reprex package (v0.3.0)}

ggplot(data = mapdata) +
geom_polygon(mapping = aes(x=long,y=lat,group=group, fill=Impressions))

[pieterjanvc]

Hi,

Welcome to the RStudio community!

In order for us to help you with your question, please provide us a minimal reproducible example where you provide a minimal (dummy) dataset and code that can recreate the issue. Once we have that, we can go from there. For help on creating a Reprex, see this guide:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

Good luck!
PJ

[twwzx]

Thank you for the feedback, I pasted 2 data sets following the guide. Hope that would help

[andresrcs]

It is better, but next time please try to make a complete self-contained reproducible example (as explained in the guide).

I think your problem is the use of merge() try with left_join() instead, see this reprex

library(tidyverse)
library(ggmap)

states <- map_data("state")

AEP <- data.frame(Impressions = c(9434L, 10060L, 5686L, 22694L, 5998L), 
                  region = as.factor(c("alabama", "arizona", "arkansas", "california", 
                                       "colorado")))

mapdata <- states %>% 
    left_join(AEP, by="region")

ggplot(data = mapdata) +
    geom_polygon(mapping = aes(x=long,y=lat,group=group, fill=Impressions))

[twwzx]

It works! Thank you for your help. And I will make sure to make a complete self-contained reproducible example in the future.