Seaborn scatterplot size based on frequency of occurrence-CodePudding

I'm trying to plot data using the Seaborn library where:

x-axis - movie release year
y-axis - movie rating (0-10, discrete)

I'm using a scatterplot at the moment. My data is in a Pandas dataframe.

Obviously because the rating data I have is discrete integers, a lot of them stack on top of each other. How can I make the size of each dot scale with the frequency of appearance in the dataset?

For instance, if the number of 6/10 ratings in 2008 is higher than any other rating/year combination, I want that dot size (or something else in the plot) to indicate this.

Is there a different plot I should use for something like this instead?

CodePudding user response：

Is there a different plot I should use for something like this instead?

I suggest visualizing this as a

But if you still prefer a

Data for reference:

url = 'https://raw.githubusercontent.com/vega/vega/main/docs/data/movies.json'
df = pd.read_json(url)[['Title', 'Release Date', 'IMDB Rating']]
df['Release Year'] = pd.to_datetime(df['Release Date']).dt.year
df['IMDB Rating'] = df['IMDB Rating'].round().astype('Int8')