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data <- read.csv("avocado.csv")
head(data)
##   X       Date AveragePrice Total.Volume   X4046     X4225  X4770 Total.Bags
## 1 0 2015-12-27         1.33     64236.62 1036.74  54454.85  48.16    8696.87
## 2 1 2015-12-20         1.35     54876.98  674.28  44638.81  58.33    9505.56
## 3 2 2015-12-13         0.93    118220.22  794.70 109149.67 130.50    8145.35
## 4 3 2015-12-06         1.08     78992.15 1132.00  71976.41  72.58    5811.16
## 5 4 2015-11-29         1.28     51039.60  941.48  43838.39  75.78    6183.95
## 6 5 2015-11-22         1.26     55979.78 1184.27  48067.99  43.61    6683.91
##   Small.Bags Large.Bags XLarge.Bags         type year region
## 1    8603.62      93.25           0 conventional 2015 Albany
## 2    9408.07      97.49           0 conventional 2015 Albany
## 3    8042.21     103.14           0 conventional 2015 Albany
## 4    5677.40     133.76           0 conventional 2015 Albany
## 5    5986.26     197.69           0 conventional 2015 Albany
## 6    6556.47     127.44           0 conventional 2015 Albany
plot(Total.Volume ~AveragePrice, data, pch = 16)

cor(data$Total.Volume, data$AveragePrice)
## [1] -0.1927524