library(tidyverse)
library(ggplot2)
library(gghighlight)
#Importing the csv file to a books dataframe
books <- read.csv("bestsellers with categories.csv")
#Viewing the dataframe
head(books)
#Identifying the column names
names(books)
[1] "Name" "Author" "User.Rating" "Reviews" "Price"
[6] "Year" "Genre"
Missing Values
#Identifying total number of missing values
sum(is.na(books))
[1] 0
There are no missing values in the data.
Statistics
#Identifying Number of books
total_books = count(books)
print(paste("There are",total_books,"books in total."))
[1] "There are 550 books in total."
#Identifying Number of books in each genre
count(books,Genre)
#Identifying the average user rating, rounded to 2 decimal places
avg_rating <- round(mean(books$User_Rating),digits =2)
#Identifying the average price, rounded to 2 decimal places
avg_price <- round(mean(books$Price),digits =2)
#Identifying the average number of reviews, rounded to 2 decimal places
avg_reviews <- round(mean(books$Reviews),digits =0)
#Identifying the highest user rating
max_rating <- max(books$User_Rating)
#Identifying the highest price
max_price <- max(books$Price)
#Identifying the highest price
max_reviews<- max(books$Reviews)
cat("For books in the Bestseller list: \nAverage user rating is",avg_rating,"and the highest user rating is",max_rating,"\nAverage price of $",avg_price,"and the highest price is $",max_price, "\nAverage number of reviews is",avg_reviews,"and the highest number of reviews is",max_reviews)
For books in the Bestseller list:
Average user rating is 4.62 and the highest user rating is 4.9
Average price of $ 13.1 and the highest price is $ 105
Average number of reviews is 11953 and the highest number of reviews is 87841
#Grouping by genre
genre <- books %>% group_by(Genre)
#Summarizing average price for for books each year in each genre
genre_stats <- genre %>% summarise(Price = mean(Price))
#Renaming the price column to Average_price
colnames(genre_stats)[which(names(genre_stats) == "Price")] <- "Average_price"
#Summarizing average number of reviews for for books each year in each genre
genre_avg_reviews <- genre %>% summarise(Reviews = mean(Reviews))
#Adding the "Reviews" column from "genre_avg_reviews" to the genre dataframe as "average_reviews"
genre_stats$Average_number_of_reviews <- genre_avg_reviews$Reviews
#Summarizing average user rating for for books each year in each genre
genre_avg_rating <- genre %>% summarise(User_Rating = mean(User_Rating))
genre_stats$Average_user_rating <- genre_avg_rating$User_Rating
genre_stats
On average,
- Fiction books receive more reviews and higher user ratings than Non-Fiction books.
- Non-Fiction books are more expensive than Fiction books.
Plots
User Rating
#plotting bar graph for user rating vs. number of reviews
ggplot(data=books,aes(x=User_Rating,y=Reviews)) + geom_bar(stat="identity") + labs(title="User Rating vs. Number of Reviews")
![](data:image/png;base64,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)
- Books that receive a higher user rating recieve more reviews.
- There is a significant increase in the number of reviews for books that have a rating of 4.5 and above.
#Grouping by user rating
by_rating_price <- books %>% group_by(User_Rating)
#Summarizing average price for each user rating value
by_rating_price <- by_rating_price %>% summarise(Price = mean(Price))
#plotting bar graph for user rating vs. price
ggplot(data=by_rating_price,aes(x=User_Rating,y=Price)) + geom_col() + labs(title="User Rating vs. Average Price")
![](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAqoAAAGlCAMAAAAF5SQQAAAC9FBMVEUAAAABAQECAgIDAwMEBAQFBQUGBgYHBwcICAgJCQkKCgoLCwsMDAwNDQ0ODg4PDw8QEBARERESEhITExMUFBQVFRUWFhYXFxcYGBgZGRkaGhobGxscHBwdHR0eHh4fHx8gICAhISEiIiIjIyMkJCQlJSUmJiYnJycoKCgpKSkqKiorKyssLCwuLi4vLy8wMDAxMTEyMjIzMzM0NDQ1NTU2NjY3Nzc4ODg5OTk6Ojo7Ozs8PDw+Pj4/Pz9AQEBBQUFCQkJDQ0NERERFRUVGRkZHR0dISEhJSUlKSkpLS0tMTExNTU1OTk5PT09QUFBRUVFSUlJTU1NUVFRVVVVWVlZXV1dYWFhZWVlaWlpbW1tcXFxdXV1eXl5fX19gYGBhYWFiYmJjY2NkZGRlZWVmZmZnZ2doaGhpaWlqampra2tsbGxtbW1ubm5vb29wcHBxcXFycnJzc3N0dHR1dXV2dnZ3d3d4eHh5eXl6enp7e3t8fHx9fX1+fn5/f3+BgYGCgoKDg4OEhISFhYWGhoaHh4eIiIiJiYmKioqMjIyNjY2Ojo6Pj4+QkJCRkZGSkpKTk5OUlJSVlZWWlpaXl5eYmJiZmZmampqbm5ucnJydnZ2enp6fn5+goKChoaGioqKjo6OkpKSlpaWmpqanp6eoqKipqamqqqqrq6usrKytra2urq6vr6+wsLCxsbGysrKzs7O0tLS1tbW2tra3t7e4uLi5ubm6urq7u7u8vLy9vb2+vr6/v7/AwMDBwcHCwsLDw8PExMTFxcXGxsbHx8fIyMjJycnKysrLy8vMzMzNzc3Ozs7Pz8/Q0NDR0dHS0tLT09PU1NTV1dXW1tbX19fY2NjZ2dna2trb29vc3Nzd3d3e3t7f39/g4ODh4eHi4uLj4+Pk5OTl5eXm5ubn5+fo6Ojp6enq6urr6+vs7Ozt7e3u7u7v7+/w8PDx8fHy8vLz8/P09PT19fX29vb39/f4+Pj5+fn6+vr7+/v8/Pz9/f3+/v7///9IYq62AAAACXBIWXMAAA7DAAAOwwHHb6hkAAAa6ElEQVR4nO2dfYBUdb3GD4ggSoRiwk1DzdJ8q6siamK+ZGYuIZEobhJmioov+W6F3AhQ18iValUsKrwZhVR6IVNEERRNVLxcdU0SBUU8ArICu+zO7Pefe2a+Oy87L+c5Z3+/2TlHns8fM2dnnvmdh+/5ePbs7LrrCCGxwKl2AUKCQVVJTKCqJCZQVRITqCqJCVSVxITQqv7YWZO+f9h5AEVnOyl2OfB76/IffeQW7+YL3w273xwPOs6rXX91moZ0s8FnPJd9xKQQ6RYqq+rFdXV1U0b1OLwlf4F+3s3pN4Tdb45v93Imd/3VaRqcy+vqbvv+7r1XZR4xKUS6hYqoukXvZjuPpe8vc/6ev0C/3HYiGXb3Ik27jf38weWf3hJkjQZnaepuqTMuxItIdTFT9f0J+/c97FepD18881N7j270No65+pGhtRrNqDrf+YXIr4f2H3jqMpETvc+8dXKE9/n2uIlT+/X8bH06cdyAU18cXKcvG90vdRL+h/O7vOXz+K2z8EfOC/mxwn1ndpW/bjaTpkNV+dSxmRelCslDw/sfOTlRlCaRwEzVEwZM/NlwZ67Ik32Gzpi2357/8o786QOveVSjGVXvcf4q051v333jgf03ymsX9n3+PVV1yIBb5xyfOuP+qedZM8fs0adD1T+kT8IT+jblls/na/u0rXSuz4sV7ju7q7x1c5k0Hapu3fX0zItShX7X44xfXNHrnKI0iQRGqq51Zoh8eNiNIkcd652M1g8Y6x15Z3Emqqo2P3XgUa0y7PNeYFnqgfQFQFpVZ4mI2/NmSR58ervI+U6Hqk19LhdJDh6Tt3weG3a5SuSQIe25WOG+s7vKWzeXSZNWNfn6N1M70Bd5hZo//Q0vPt5ZW5gmkcBI1fd7nKQfvOv8OnV33n94Rz53HanvADjOUR+K7GiT1Inw4XxVv5AK7XO1vJw+cT6ZUVVqhqQuI/+WWz6fu5x/ikxKqdYRK9p3dle5dfMyaRo6mp2XzLzIK7Q4fZp+q+HdwjSJBGYXAD/p2XPYzS+ndFB2TX0+zUb1HYBpo5wrvA8eu+6sg3t0VvWMVGjw1fKX1KWnrMuqOttZKdfs1ZpbPp8T+v9+zpxJzsRsrHjfmV3l1s3LpEm/A1D3q2dT2/oir9Csjn9ZUZpEgi6o+mb6/qH0OwCvTz+ld4875FnnV8+n8Y78yGw0c616Tu/tcp0zfNL9j3ZW9azUk56qc50XvY31WVU39fqpHDBBcsvn8WaHRvskMrGifWd3lVs3L5Mm82VVCn2RV+iX3qf+NIVpEglCqzrLeTJ9f6f3iXjTqh2eCsfunnSdhtRjjzxSUtWfOWs29ky9Ffp/pVVd4fxZUleXGVXlq8NeSF3HZpfP2/00Z3nqbpLzj0yscN+5XeXWzcukKanqP5zHvY11E14sTJNIEFrV13b5eupa8IOD9m6Rhc5fvM3L+yXky4duFnlhlxtKqvoL5+XnnLu9jelpVfeQAlVb9jvT2/huTtWGHt/zvm7KWz7HEfun7152LszGCvad21XeurmM7qCUqlv2OtvbmOp91ihIk0gQ/mcApjkHXjP9kgG9Fnpfq++71+SG7/S6VGRJn8Nv+9n+g9aVVHW289C2QUPumHPeZ5yL13sSzXq9s6rye+fshtpjnJ9nXvhezx43Sf7ydx/xkD7zstPhzyEDdmRiBfvO21Vu3VwmTUlVvf+kau6+vndtUZpEgi78uMrjZx7Q9wvfSb9BvmrEoL6HTvc+Tcvzpw8cNPp1KanqC85R8s8T+33uqo/G9Zsjbw3b7ZcFqsp/Hznw3FX6dXea4c7/dlr+p84cfeImZ4VuTEqdcTtiBfvO7Spv3WwmTWlVZe7x/Q764faiNIkEUfjJqkRD6kvxBc6zMVmXVIUoqCpDhzyz9YUjvxybdUk1iISqq49zHOera2OzLqkGkVBVZO0LTbFal3Q/EVGVEARVJTGBqpKYQFVJTKCqJCZQVRITqCqJCVSVxISwqrpl2VH+qS6TaK7AopUomtxuf80PWuyv6bZvs7/mxkocJdma2cr8n+9U1QpU1TZU1aWq1qGqLlW1D1V1qap1qKpCVa1CVW1DVV2qah2q6lJV+1BVl6pah6oqVNUqVNU2VNWlqtahqi5VtQ9VdamqdaiqQlWtQlVtQ1VdqmodqupSVRuc54uNPVBVl6ragKoWQVUtQ1UVqmoVqmobqupSVapKVS1DVRWqahWqahuq6lJVqkpVLUNVFapqFapqm3CqPjNx7KT3RVZNvODe7F85K782VbUMVVUCqLphTGPzzP+SxPiVzTcspqq+UFXbhFJ18VSRtWNlxfUiT02mqr5QVduEUrX5I5EnJsnCepE1l3kfb509e/bzW8uSKP9Ul0m2VmDRShRtr0DRbW1WlvFX1cYeLBXtjOzIbG3HqnosGfeqzL3Xuxao9T5Yf/TRR9f7xkkE8Ve12u0C0NZx76dq05Sr1ogsuMs7q07IPFb+jM0LAMvwAkAJcAHQevV97d7diptEnua1qj9U1TahVH3y5vRdYtzq5C2LqKovVNU2oVS9r8bjfJFXr7wkfXqlquWhqrbhd6tcqkpVqaplqKpCVa1CVW1DVV2qSlWpqmWoqkJVrUJVbUNVXapKVamqZaiqQlWtQlVtQ1VdqkpVu0lV/8kHGT1Vpar2oarmUNUiqKplqKpCVa1CVW1DVV2qSlWpqmWoqkJVrUJVbUNVXapKVamqZaiqQlWtQlVtQ1VdqkpVqaplqKpCVa1CVW1DVV2qSlWpqmWoqkJVrUJVbUNVXapKVamqZaiqQlWtQlVtQ1VdqkpVP1aqht0JVbUNVXWp6s6iaktZkuWf6jLtiaKHgKoBFg1SNOxOShQ1x85EjecF2VGJf7y0Zbaau6jqB2XZUf6pLpNoLnoIqBpg0SBFw+4kuT3AoiHZ2GJlGeN5QTYVHyVzZGtmq6mLqpY/Y/MCwDK8AFB4reoLVQ0BVXWpqg2oahFU1TJUVaGqvlDVEFBVl6ragKoWQVUtQ1UVquoLVQ0BVXWpqg2oahFU1TJUVaGqvlDVEFBVl6ragKoWQVUtQ1UVquoLVQ0BVXWpqg2oahFU1TJUVaGqvlDVEFBVl6ragKoWQVUtQ1UVquoLVQ0BVXWpqg2oahFU1TJUVaGqvlDVEFBVl6ragKoWQVUtQ1UVquoLVQ0BVXWpqg2oahFU1TJUVaGqvlDVEFBVl6ragKoWQVUtQ1UVquoLVQ1BJFRd1urdXFtTU9NAValqOaKg6rox27zb2qbW1gRVparliICqt46u8VRtruUFAFX1IwKqinzLU/XN2ivGTtnkfdBUX1+/bHtZEuWf6jLtbUUPAVUDLBqkaNidlChqjp2JGs8L0lyJf7y05jaDqvratI2JO6Z7H7w/YsSI3ybK0l7+qS4jxYsCVQMsGqRo2J2UKGqOnTWN5wVJVuTQJzNbOwKrmqJxDC8AfHfCCwDbdOUCoLFRZHX2erX82lTVMlRVCa7q0vEbknfOpKpUtRyRUVXmXTRuxjaqSlXLEQlViym/9k6mauUNoKoKVfWFqoaAqrpU1QZUtQiqWg1Vo1CUqrpUNR5FqapLVeNRlKq6VDUeRamqS1XjUZSqulQ1HkWpqktV41GUqroVU9XG8a28AVRVoaqGx7fyBlBVhaoaHt/KG0BVFapqeHwrbwBVVaiq4fGtvAFUVaGqhse38gZQVYWqGh7fyhtAVRWqanh8K28AVVWoquHxrbwBVFWhqobHt/IGUFWFqhoe38obQFUVqmp4fCtvgKdqPIpSVZeqxqMoVXWpajyKUlWXqsajKFV1qWpEivovcR5VdalqRIr6L0FVU1DVSBT1X4KqpqCqkSjqvwRVTUFVI1HUfwmqmoKqRqKo/xJUNQVVjURR/yWiqmprWdrLP9Vl2pNFD4GxBVkUrIH3EixhTDIqRf2XOK+t+CiZI4nMVgvPqn5L2EiYwrOqwgsAw+NrXANCVRWqanh8jWtAqKpCVQ2Pr3ENCFVVqKrh8TWuAaGqClU1PL7GNSBUVaGqhsfXuAaku1T1DwRIxFBVPLawUNVuKOofoKrBoKrdUNQ/QFWDQVW7oah/gKoGg6p2Q1H/AFUNBlXthqL+AaoajDiralyUqipU1XcJCwlcFCSoqlJK1c2zpsjKBFWFewmUwEVBgqoqJVR9+7BBjgw7fA1VjYYBVFUpoeo3zk/0knUnnU1Vo2EAVVVKqPqJ56SXyGMDqGo0DKCqSglV91uSUnXBZ6hqNAygqkoJVS8+eXMveeXzl1PVaBhAVZUSqn548q7O4B6jtlHVaBhAVZWS76su/82Dr/uKSlWDJ3BRkKCqSglV2665UGTodc1UNRoGUFWlhKo3D5otcs++P6Cq0TCAqiolVD3w/tTtHz5NVaNhQJxUxTXC4qvq3k+nbp8bSFWjYQBVVUqoes7XNos01YyiqtEwgKoqJVR9/4t7DDuh/yHvUNVoGEBVlVJvViX/59Yp89p8TaWqgRO4KEhQVaVQ1ZfekZc6oKrRMICqKoWqOteJ0wFVjYYBVFUpVLWlTVo6oKrRMICqKsXXqttGrPOVlKqGS+CiIEFVlRJfVp12f5GYy1q9m1UTL7g3SVXDJnBRkPh4qYoTnfFVdfkJ0/++1CP3yLox20QS41c237CYqoZN4KIgQVWVEqoWfVl16+gaT9UV14s8NZmqhk3goiBBVZVg/3P1tzxVF9aLrLnM+2DzjTfeuKClLMkW/zblX1me9kTRQ2BsARYNUtRCAhcFiR2xKZqwUrQz0pbZyvyoX56qydKqzr1XZEOt98HGSy+9dH75P4kR5O+BhKUif2Glm/5wCS6KEjtZ0c6U/wsrTRcO6H3q6lKqLrjLO6tO4AVA2AQuChK8AFAKLwAu7/fjuiFHFp5YU6quuEnkaV6rhk7goiBBVZVCVffzhJzvvFFC1cS41clbFlHVsAlcFCSoqlKoao/FIs3O8hKqyqtXXnJfO1UNm8BFQYKqKkU/A7A8c+OPmQFhoarGNahq1wwIC1U1rvExVHX4yJEj0zcjqWo0DKCqSqGqo3NQ1WgYQFUV/ipgw8HCBC4KElRVoaqGg4UJXBQkqKpCVQ0HCxO4KEhQVYWqGg4WJnBRkKCqClU1HCxM4KIgQVUVqmo4WJjARUGCqipU1XCwMIGLggRVVaiq4WBhAhcFCaqqUFXDwcIELgoSVFWhqoaDhQlcFCSoqkJVDQcLE7goSFBVhaoaDhYmcFGQoKoKVTUcLEzgoiBBVRWqajhYmMBFQYKqKlTVcLAwgYuCBFVVqKrhYGECFwUJqqpQVcPBwgQuChJUVaGqhoOFCVwUJKiqQlUNBwsTuChIUFWFqhoOFiZwUZCgqgpVNRwsTOCiIEFVFapqOFiYwEVBgqoqVNVwsDCBi4IEVVWoquFgYQIXBQmqqlBVw8HCBC4KElRVoaqGg4UJXBQkqKpCVQ0HCxO4KEhQVYWqGg4WJnBRkKCqSldVNfvDJWHZqf/CSmyKdv9fWOFZNbeEhQQuChI8qyq8ADAcLEzgoiBBVRWqajhYmMBFQYKqKlTVcLAwgYuCBFVVqKrhYGECFwUJqqpQVcPBwgQuChJUVaGqhoOFCVwUJKiqQlUNBwsTuChIUFWFqhoOFiZwUZCgqgpVNRwsTOCiIEFVFapqOFiYwEVBgqoqVNVwsDCBi4IEVVWoquFgYQIXBQmqqlBVw8HCBC4KElRVoaqGg4UJXBQkqKpCVQ0HCxO4KEhQVYWqGg4WJnBRkKCqClU1HCxM4KIgQVUVqmo4WJjARUGCqipU1XCwMIGLggRVVaiq4WBhAhcFCaqqUFXDwcIELgoSVFWhqoaDhQlcFCSoqkJVDQcLE7goSFBVhaoaDhYmcFGQoKoKVTUcLEzgoiBBVRWqajhYmMBFQYKqKlTVcLAwgYuCBFVVqKrhYGECFwUJqqpQVcPBwgQuChJUVaGqhoOFCVwUJKiqQlUNBwsTuChIUFUlhKrX1tTUNFDVsAlcFCSoqhJC1dqm1tYEVQ2bwEVBgqoqwVVtrs3/yMyAsFBV4xo7k6pv1l4xdsomqho2gYuCBFVVgqv62rSNiTumexsf1NbWPtBWlvY2/zblX+mzZrLoITC2IIsGKGohgYuiRGyKJm3UKECyh35HYFVTNI7xbrZMnTp1UXNZks3+bcq/sjztiaKHwNgCLBqkqIUELooSiZgUbbFTtDPSltsMqmpjo8jq7PWq2efVsPACwLjGznQBsHT8huSdM6lq2AQuChJUVQnxZtW8i8bN2EZVwyZwUZCgqgq/W2U4WJjARUGCqipU1XCwMIGLggRVVaiq4WBhAhcFCaqqUFXDwcIELgoSVFWhqoaDhQlcFCSoqkJVDQcLE7goSFBVhaoaDhYmcFGQoKoKVTUcLEzgoiBBVRWqajhYmMBFQYKqKlTVcLAwgYuCBFVVqKrhYGECFwUJqqpQVcPBwgQuChJUVaGqhoOFCVwUJKiqQlUNBwsTuChIUFWFqhoOFiZwUZCgqgpVNRwsTOCiIEFVFapqOFiYwEVBgqoqVNVwsDCBi4IEVVWoquFgYQIXBQmqqlBVw8HCBC4KElRVoaqGg4UJXBQkqKpCVQ0HCxO4KEhQVYWqGg4WJnBRkKCqClU1HCxM4KIgQVUVqmo4WJjARUGCqipU1XCwMIGLggRVVaiq4WBhAhcFCaqqUFXDwcIELgoSVFWhqoaDhQlcFCSoqkJVDQcLE7goSFBVhaoaDhYmcFGQoKoKVTUcLEzgoiBBVRWqajhYmMBFQYKqKl1VtbUs7a3+bcq/0mfNZNFDYGxBFg1Q1EICF0WJZEyKttkp2hlJZLZaeFb1W8JCAhcFCZ5VFV4AGA4WJnBRkKCqClU1HCxM4KIgQVUVqmo4WJjARUGCqipU1XCwMIGLggRVVaiq4WBhAhcFCaqqUFXDwcIELgoSVFWhqoaDhQlcFCSoqkJVDQcLE7goSFBVhaoaDhYmcFGQoKoKVTUcLEzgoiBBVRWqajhYmMBFQYKqKlTVcLAwgYuCBFVVqKrhYGECFwUJqqpQVcPBwgQuChJUVaGqhoOFCVwUJKiqQlUNBwsTuChIUFWFqhoOFiZwUZCgqgpVNRwsTOCiIEFVFapqOFiYwEVBgqoqVNVwsDCBi4IEVVWoquFgYQIXBQmqqlBVw8HCBC4KElRVoaqGg4UJXBQkqKpCVQ0HCxO4KEhQVYWqGg4WJnBRkKCqClU1HCxM4KIgQVUVqmo4WJjARUGCqipU1XCwMIGLggRVVaiq4WBhAhcFCaqqUFXDwcIELgoSVFWhqoaDhQlcFCSoqhJC1VUTL7g3SVXDJnBRkKCqSnBVE+NXNt+wmKqGTeCiIEFVleCqrrhe5KnJVDVsAhcFCaqqBFd1Yb3ImsuoatgELgoSVFUJrurce0U21HobG04++eS728si7f5tyr/SZ00pegiMLciiAYpaSOCiKBGbolZqFB2lDK2BVV1wl3dWneBtNNXX1y/bXpZE+ae6THtbBRbduYu22l+zuRL/eMkVDazqiptEng50rWqfEhcA5lSiaHK7/TW9CwD7tG+zv+bGShylLr0DMG518pZFVNUXqmqbLr2v+uqVl9zXTlV9oaq2qex3q+xDVW1DVV2qah2qqlBVq1BV21BVl6pah6q6VNU+VNWlqtahqgpVtQpVtQ1VdamqdaiqS1XtQ1VdqmodqqpQVatQVduYq9q9zHmi2g0C8utl1W4QkLufq3aDgMx8sfCRaKs6+rZqNwjImfXVbhCQr8yqdoOAHHt/4SNU1QpU1TZUtUJQVdvETdX3Nle7QUDWb8GZSPBOU7UbBOSdjwofibaqhGShqiQmRFTVv44///bm9Na1NTU1DVVu40vzw3rf6fclRZFM0YhPNFevYKLRVPXf492PfviH9GZtU2trosp1fKm/OH3X+fclRZGOolGfaLZe4USjqerTvxX5y89TW8211e4CeOYqNaDz70uKIJmiEZ9orl7hRKOpqsiHL/0g/X2VN2uvGDtlU7XblGfTlavUgM6/Lyl6ZItGfKK5eoUTjaqqz1526frU/WvTNibumF7tNmVpn/ziW2pA9vclRZNc0YhPNFevcKJRVVVkfvbc3zimmj18efge6TAg+/uSokmuaIoITzSF1iucaDRVffAxkVe/n9pqbBRZHd2T1Yxzzz1nxLkfSuHvS4ocuaIRn2iuXuFEo6nqkqvf3XrHDK/39qXjNyTvnFntPn6kT1aN2zv/vqQo0lE04hPN1CueaDRVlQe+V3tbk8jIV2TeReNmbKt2HT/SBnhFO/2+pCiSKRrxiXbUK55oRFUlpBCqSmICVSUxgaqSmEBVSUygqiQmUFUSE6iqMSdelL4bXOcfq3U8dvviH3OPvP+RtDgvVbDZxwuqakxQVY9bvnz5o6N7Pp97YZ20XfdOJat9rKCqxviqmvu2UO0Zqdsdu+V+qOlEIDfpBFU1Jk/Vv32p7wEzRLZcMqT/WWu94S4/fUQ2pqrKgHvkX9/c5xMnvSTHOM4ZqQuAXvMP73vQn0XcUXsePc/ZWpV/QxygqsbkVH2r903/vN15Wk75ypPPjT1sszjHz1mbjaVV3XJb/7fl0JMXPT58aPqsmlZ13z+tOne3Zhn29eUPDKSqZaGqxuRUfazHGyIPr1m+62aRxKBZ4kzLi6W/rHJ2WSDtdf8W+d3eOVW9VKPzxpI+H4jcRlXLQlWNyam6/fg+I+vflt84vTycn4jz97xY+suqB0/ZZ6s0//FH39ozT9VHRD5w3ph5mBd6gqqWhaoac8oF6bs960Xan/rxf/ae/+DgjmecpXkxvVZ9x3nyoy8dc/tDs/NUfSKt6ozDvaeXUNWyUFVjrjgk9WfAX3KekEWpT/jfPLuxxysi64atLKWqOPP/1nuTyJwiVR/ps1GkjqqWhaoa80b/0x5c8sv9TkvK4z3vWjV3z6ky6uCFi046PFFS1U/MWubMenve/ru7MvzyzXmqth9Ts2LeQU6Ef+i5ylBVc1759mf6HjY5dTr8+Wf77H9zm2y7dL8BI9eUvACQY4+RqYP3Gv3aoUNl1sBRearK+ppPnvLHnpH+HwmqClWNCm6Dd0Kd/blq14guVDUqbN/r2vdePnRqtWtEF6paWZac1sEcGF02bPfP3tjSDZ1iClUlMYGqkphAVUlMoKokJlBVEhOoKokJVJXEBKpKYsL/A+Asl6yvblBbAAAAAElFTkSuQmCC)
On average, books with a user rating of 4.5 tend to be the most expensive.
Price
#plotting scatter plot for price vs. number of reviews
##geom_point() creates a scatter plot
#facet_wrap(~Genre) groups the data by Genre
#gghighlight(Reviews>25000) will highlight books with more than 25,000 reviews
ggplot(data=books,aes(x=Price,y=Reviews)) + geom_point() + labs(title="Price vs. Number of Reviews") + gghighlight(Price<=25)
![](data:image/png;base64,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)
Generally, books priced at or under $25 receive the most reviews.
#plotting scatter plot for price vs. number of reviews
#Highlighting books with more than 25,000 reviews
ggplot(data=books,aes(x=Price,y=Reviews)) + geom_point() + facet_wrap(~Genre) + labs(title="Price vs. Number of Reviews by Genre") + gghighlight(Reviews>25000)
![](data:image/png;base64,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)
Highlighted above are the books that received over 25,000 reviews.
Year
#Grouping by year
by_year <- books %>% group_by(Year)
#Summarizing average price for for books each year
by_year_price <- by_year %>% summarise(Price = mean(Price))
#Summarizing average price for for books each year
by_year_reviews <- by_year %>% summarise(Reviews = mean(Reviews))
#plotting bar graph for year vs. average number of reviews
#You have to specify stat="identity" for this kind of dataset.
#labs(title=" ") sets the title
ggplot(data=by_year_reviews,aes(x=Year,y=Reviews)) + geom_col() + labs(title="Average Number of Reviews Per Year")
![](data:image/png;base64,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)
After mid-2011 the average number of reviews received increased significantly.
#plotting bar graph for year vs. average price
#You have to specify stat="identity" for this kind of dataset.
#labs(title=" ") sets the title
ggplot(data=by_year_price,aes(x=Year,y=Price)) + geom_col() + labs(title="Average Price Per Year")
![](data:image/png;base64,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)
The average price for an Amazon Top 50 Bestseller has remained between $10 to $15 between 2009-2019.
Summary of Data Analysis
There are 550 books in total.
- Fiction: 240
- Non-Fiction: 310
For books on the Bestseller list in the period from 2009-2019,
- Average user rating is 4.62 and the highest user rating is 4.9
- Average price of $13.10 and the highest price is $105.00
- Average number of reviews is 11953 and the highest number of reviews is 87841
- Fiction books receive more reviews and higher user ratings than Non-Fiction books.
- Non-Fiction books are more expensive than Fiction books.
Relationship between Price, User Rating, Number of Reviews and Year of Release
- The average price for an Amazon Top 50 Bestseller has remained between $10 to $15 between 2009-2019.
- Books priced at or under $25 receive the most reviews, regarless of genre.
- After mid-2011 the average number of reviews received increased significantly.
- Books that have a rating of 4.5 and above receive significantly higher reviews.
- The majority of books receive less than 25,000 reviews.
- Books that receive a higher user rating received more reviews.
- Books with a user rating of 4.5 tend to have the highest average price.
---
title: "Amazon Bestsellers Data Analysis"
output: html_notebook
---

```{r}
library(tidyverse)
library(ggplot2)
library(gghighlight)

#Importing the csv file to a books dataframe
books <- read.csv("bestsellers with categories.csv")

#Viewing the dataframe
head(books)

#Identifying the column names
names(books)
```
### Correcting Formatting Issues
```{r}
# Change the column name from User.Rating to User_Rating
names(books)[names(books) == "User.Rating"] <- "User_Rating"
```

### Missing Values
```{r}
#Identifying total number of missing values
sum(is.na(books))
```
There are no missing values in the data.


## Statistics
```{r}
#Identifying Number of books
total_books = count(books)

print(paste("There are",total_books,"books in total."))

#Identifying Number of books in each genre
count(books,Genre)
```
```{r}
#Identifying the average user rating, rounded to 2 decimal places
avg_rating <- round(mean(books$User_Rating),digits =2)

#Identifying the average price, rounded to 2 decimal places
avg_price <- round(mean(books$Price),digits =2)

#Identifying the average number of reviews, rounded to 2 decimal places
avg_reviews <- round(mean(books$Reviews),digits =0)

#Identifying the highest user rating
max_rating <- max(books$User_Rating)

#Identifying the highest price
max_price <- max(books$Price)

#Identifying the highest price
max_reviews<- max(books$Reviews)

cat("For books in the Bestseller list: \nAverage user rating is",avg_rating,"and the highest user rating is",max_rating,"\nAverage price of $",avg_price,"and the highest price is $",max_price, "\nAverage number of reviews is",avg_reviews,"and the highest number of reviews is",max_reviews)
```

```{r}
#Grouping by genre
genre <- books %>% group_by(Genre)

#Summarizing average price for for books each year in each genre
genre_stats <- genre %>% summarise(Price = mean(Price))

#Renaming the price column to Average_price
colnames(genre_stats)[which(names(genre_stats) == "Price")] <- "Average_price"

#Summarizing average number of reviews for for books each year in each genre
genre_avg_reviews <- genre %>% summarise(Reviews = mean(Reviews))

#Adding the "Reviews" column from "genre_avg_reviews" to the genre dataframe as "average_reviews" 
genre_stats$Average_number_of_reviews <- genre_avg_reviews$Reviews

#Summarizing average user rating for for books each year in each genre
genre_avg_rating <- genre %>% summarise(User_Rating = mean(User_Rating))

genre_stats$Average_user_rating <- genre_avg_rating$User_Rating

genre_stats
```
On average,

- Fiction books receive more reviews and higher user ratings than Non-Fiction books.
- Non-Fiction books are more expensive than Fiction books.


## Plots

### User Rating

```{r}
#plotting bar graph for user rating vs. number of reviews
ggplot(data=books,aes(x=User_Rating,y=Reviews)) + geom_bar(stat="identity") + labs(title="User Rating vs. Number of Reviews")
```

- Books that receive a higher user rating recieve more reviews.
- There is a significant increase in the number of reviews for books that have a rating of <b> 4.5 and above.</b> 

```{r}
#Grouping by user rating
by_rating_price <- books %>% group_by(User_Rating)

#Summarizing average price for each user rating value
by_rating_price <- by_rating_price %>% summarise(Price = mean(Price))

#plotting bar graph for user rating vs. price
ggplot(data=by_rating_price,aes(x=User_Rating,y=Price)) + geom_col() + labs(title="User Rating vs. Average Price")
```

On average, books with a user rating of <b>4.5</b> tend to be the most expensive.

### Price
```{r}
#plotting scatter plot for price vs. number of reviews
ggplot(data=books,aes(x=Price,y=Reviews)) + geom_point() + labs(title="Price vs. Number of Reviews") + gghighlight(Price<=25)
```
Generally, books priced at or under <b>$25</b> receive the most reviews.


```{r}
#plotting scatter plot for price vs. number of reviews
#Highlighting books with more than 25,000 reviews 
ggplot(data=books,aes(x=Price,y=Reviews)) + geom_point() + facet_wrap(~Genre) + labs(title="Price vs. Number of Reviews by Genre") + gghighlight(Reviews>25000)

```

Highlighted above are the books that received over 25,000 reviews. 

## Year
```{r}
#Grouping by year
by_year <- books %>% group_by(Year)

#Summarizing average price for for books each year
by_year_price <- by_year %>% summarise(Price = mean(Price))

#Summarizing average price for for books each year
by_year_reviews <- by_year %>% summarise(Reviews = mean(Reviews))

#plotting bar graph for year vs. average number of reviews
ggplot(data=by_year_reviews,aes(x=Year,y=Reviews)) + geom_col() + labs(title="Average Number of Reviews Per Year")
```
<b>After mid-2011</b> the average number of reviews received increased significantly. 
```{r}
#plotting bar graph for year vs. average price
ggplot(data=by_year_price,aes(x=Year,y=Price)) + geom_col() + labs(title="Average Price Per Year")
```
The average price for an Amazon Top 50 Bestseller has remained <b> between $10 to $15</b> between 2009-2019.

# Summary of Data Analysis

There are <b>550</b> books in total.

- Fiction: 240
- Non-Fiction: 310

For books on the Bestseller list in the period from 2009-2019,

- Average user rating is 4.62 and the highest user rating is 4.9 
- Average price of $13.10 and the highest price is $105.00 
- Average number of reviews is 11953 and the highest number of reviews is 87841
- Fiction books receive more reviews and higher user ratings than Non-Fiction books.
- Non-Fiction books are more expensive than Fiction books.

### Relationship between Price, User Rating, Number of Reviews and Year of Release

- The average price for an Amazon Top 50 Bestseller has remained <b> between $10 to $15</b> between 2009-2019.
- Books priced at or under <b>$25</b> receive the most reviews, regarless of genre.
- <b>After mid-2011</b> the average number of reviews received increased significantly. 
- Books that have a rating of <b> 4.5 and above</b> receive significantly higher reviews.
- The majority of books receive less than 25,000 reviews.
- Books that receive a higher user rating received more reviews.
- Books with a user rating of <b>4.5</b> tend to have the highest average price. 






