Added: Priscilla Kwon - Date: 05.12.2021 13:07 - Views: 41373 - Clicks: 9922
As an introduction to the package, it is an interesting and useful exercise to visualize the distribution of Matchmaking Rating MMR of the top Starcraft II players. For this exercise, we will limit our scope to the European region and investigate its Grandmaster league i. To begin, we will load the SC2API package and ggplot2, another package that is extremely useful for plotting and visualization. To receive this token, create a client in the Blizzard Developer Portal and obtain a valid client ID and client secret.
Of course, you must Starcraft matchmaking rating the arguments with your own id and secret.
To see other choices for these arguments, see the help documentation in? Since leagues are often separated into tiers and further separated into divisions, we must specify which ladder ID we are actually looking for. Of course, there is only one tier and one division for Grandmaster league and so finding the appropriate ladder ID is relatively easy.
For other leagues, finding a particular ladder ID may be slightly more difficult but can be completed using list indexing. To retrieve the MMRs of players in past seasons, the above functions are necessary. However, since the grandmaster league is, in some sense, special, there is an alternative function we can use to retrieve the MMRs of players currently in grandmaster that is, in the current season :.
That is. For this reason, it is important to refer to the documentation. Since we now have the MMRs of players from season 43, we can plot the distribution as a histogram using the ggplot2 package. Although this is useful, it would also be interesting to look at the distribution by player race.
First, we will obtain the race of each player in the league. This is accomplished using the sapply function. Then, we create a simple data frame with the MMR and races. Since there are so few random players, we will filter these out from the dataset at the time of writing there is a single player in the Starcraft matchmaking rating league of Europe. Now, we will once again plot a histogram and look at the separate race distributions using ggplot2 with some arguments to make the plot a little more visually appealing.
Another way of visualizing these distributions is to plot them on the same graph and use a statistical method to create a smoothed density estimate. The below plot shows a smoothed density estimate using a Gaussian kernel and an adjusted bandwidth. Visualization Overall distribution Since we now have the MMRs of players from season 43, we can plot the distribution as a Starcraft matchmaking rating using the ggplot2 package.
Distribution by race First, we will obtain the race of each player in the league.Starcraft matchmaking rating
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MMR Distribution in Starcraft II