用 R 绘制一段时间内的销售额

Question

I am trying to show the top 100 sales on a scatterplot by year. I used the below code to take top 100 games according to sales and then set it as a data frame.

top100 <- head(sort(games$NA_Sales,decreasing=TRUE), n = 100)
as.data.frame(top100)

I then tried to plot this with the below code:

ggplot(top100)+
  aes(x=Year, y = Global_Sales) +
    geom_point()

I bet the below error when using the subset top100 Error: data must be a data frame, or other object coercible by fortify() , not a numeric vector

if i use the actual games dataseti get the plot attached.

Any ideas?

Answer 1

As pointed out in comments by @CMichael, you have several issues in your code. In absence of reproducible example, I used iris dataset to explain you what is wrong with your code.

top100 <- head(sort(games$NA_Sales,decreasing=TRUE), n = 100)

By doing that you are only extracting a single column.

The same command with the iris dataset:

> head(sort(iris$Sepal.Length, decreasing = TRUE), n = 20)
 [1] 7.9 7.7 7.7 7.7 7.7 7.6 7.4 7.3 7.2 7.2 7.2 7.1 7.0 6.9 6.9 6.9 6.9 6.8 6.8 6.8

So, first, you do not have anymore two dimensions to be plot in your ggplot2 . Second, even colnames are not kept during the extraction, so you can't after ask for ggplot2 to plot Year and Global_Sales .

So, to solve your issue, you can do (here the example with the iris dataset):

top100 = as.data.frame(head(iris[order(iris$Sepal.Length, decreasing = TRUE), 1:2], n = 100))

And you get a data.frame of of this type:

> str(top100)
'data.frame':   100 obs. of  2 variables:
 $ Sepal.Length: num  7.9 7.7 7.7 7.7 7.7 7.6 7.4 7.3 7.2 7.2 ...
 $ Sepal.Width : num  3.8 3.8 2.6 2.8 3 3 2.8 2.9 3.6 3.2 ...

> head(top100)
    Sepal.Length Sepal.Width
132          7.9         3.8
118          7.7         3.8
119          7.7         2.6
123          7.7         2.8
136          7.7         3.0
106          7.6         3.0

And then if you are plotting:

library(ggplot2)
ggplot(top100, aes(x = Sepal.Length, y = Sepal.Width)) + geom_point()

Warning Based on what you provided in your example, I will suggest you to do:

top100 <- as.data.frame(head(games[order(games$NA_Sales,decreasing=TRUE),c("Year","Global_Sales")], 100))

However, if this is not satisfying to you, you should consider to provide a reproducible example of your dataset How to make a great R reproducible example