Avocado - Exploratory Analysis

urlfile<-'https://raw.github.com/utjimmyx/resources/master/avocado_HAA.csv'
data<-read.csv(urlfile, fileEncoding="UTF-8-BOM")
summary(data)

##         date       average_price    total_volume            type      
##  Length   :12628   Min.   :0.500   Min.   :    253   Length   :12628  
##  N.unique :  154   1st Qu.:1.100   1st Qu.:  15733   N.unique :    2  
##  N.blank  :    0   Median :1.320   Median :  94806   N.blank  :    0  
##  Min.nchar:    8   Mean   :1.359   Mean   : 325259   Min.nchar:    7  
##  Max.nchar:   10   3rd Qu.:1.570   3rd Qu.: 430222   Max.nchar:   12  
##                    Max.   :2.780   Max.   :5660216                    
##       year          geography    
##  Min.   :2017   Length   :12628  
##  1st Qu.:2018   N.unique :   41  
##  Median :2019   N.blank  :    0  
##  Mean   :2019   Min.nchar:    5  
##  3rd Qu.:2020   Max.nchar:   20  
##  Max.   :2020

library(plyr)
str(data)

## 'data.frame':    12628 obs. of  6 variables:
##  $ date         : chr  "2017/12/3" "2017/12/3" "2017/12/3" "2017/12/3" ...
##  $ average_price: num  1.39 1.44 1.07 1.62 1.43 1.58 1.14 1.77 1.4 1.88 ...
##  $ total_volume : int  139970 3577 504933 10609 658939 38754 86646 1829 488588 21338 ...
##  $ type         : chr  "conventional" "organic" "conventional" "organic" ...
##  $ year         : int  2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 ...
##  $ geography    : chr  "Albany" "Albany" "Atlanta" "Atlanta" ...

# Let's build a simple histogram
hist(data$average_price ,
     main = "Histogram of average_price",
     xlab = "Price in USD (US Dollar)")

library(ggplot2)
ggplot(data, aes(x = average_price, fill = type)) + 
  geom_histogram(bins = 30, col = "red") + 
  scale_fill_manual(values = c("blue", "green")) +
  ggtitle("Frequency of Average Price - Oragnic vs. Conventional")

Simple EFA with ggplot

ggplot() + geom_col(data, mapping = aes(x = reorder(geography,total_volume), y = total_volume, fill = year )) + xlab(“geography”)+ ylab(“total_volume”)+ theme(axis.text.x = element_text(angle = 90, size = 7))

Sample response for year 2017 - The plot shows that Los Angels has the highest amount of sales in 2017.

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