Mini_assignment 4

library(readr)

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library(tidyverse)

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## ✔ purrr   0.3.4

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library(sf)

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library(tmap)

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library(leaflet)
library(here)

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## here() starts at D:/Georgia Tech/Spec topic_/MIni_assignment 4

library(tidycensus)

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Yelp <- read.csv("coffee.csv", head = TRUE)

bxplot <- ggplot(data = Yelp) +
  geom_boxplot(aes(x=avg_rating, y=hhincome),
               color="black",fill="white")
library(plotly)

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## 
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ggplotly(bxplot)

## Warning: Continuous x aesthetic -- did you forget aes(group=...)?

bcplt2 <- ggplot(data = Yelp) +
  geom_boxplot(aes(x = avg_rating, y=hhincome), 
               color = "black", fill = "white") +
  facet_wrap(~county) +
  scale_fill_brewer(palette = "Blues")

plotly::ggplotly(bcplt2)

## Warning: Continuous x aesthetic -- did you forget aes(group=...)?

mycols <- c('pct_pov_log' = "% residents under poverty",
            'hhincome' = "Median Annual Househol Income",
            'pct_white' = "Percent White Resident",
            'race.tot' = "Total Population")

library(ggpubr)

## Warning: package 'ggpubr' was built under R version 4.2.1

Yelp %>% 
  pivot_longer(cols = names(mycols), names_to = "variable", values_to = "value") %>% 
  ggplot(data= ., mapping = aes(x= review_count_log, y = value))+
  geom_point(aes(color = county))+
  geom_smooth(aes(color= county), method = "lm", se = F)+
  ggpubr::stat_cor(method = "pearson") +
  facet_wrap(~variable, scales = "free_y", labeller= as_labeller(mycols)) +
  theme_light()

## `geom_smooth()` using formula 'y ~ x'