How can I add a column indicating clusters on my original df? Python

Question

I have clustered pitchers in baseball based off of averages of advanced metrics. I am working with statcast data, so every data point is a pitch thrown as follows:

pitcher_name	batter_name	spin_rate	release_speed	release_position
derek	alan	2000	90	-1.05
derek	alan	2100	88	-1.03
...	...	...	...	...

To cluster pitchers, I standardized and used kmeans from sklearn to cluster based on averages of advanced metrics. The new df contains no duplicate names of pitchers, just a map from each pitcher to their respective clusters.

What I want to do is add the cluster number of each pitcher to the original dataframe. That way I can calculate batting averages based on subsets.

I was hoping to get something like this:

pitcher_name	batter_name	spin_rate	release_speed	release_position	cluster
derek	alan	2000	90	-1.05	0
derek	phil	2100	88	-1.03	0
stevie	alan	1800	94	1.09	2

Note that I have already created a cluster map, such that for any given cluster, I can find the players in that group.

Does anybody have any advice?

Answer 1

If you already have a dataframe that has the mapping between the pitcher and their cluster you can simply join this dataframe to your original dataframe using merge:

original_df.merge(cluster_mapping, on="pitcher_name")

Answer 2

Assuming you have something like this:

from sklearn.cluster import KMeans

kmeans = KMeans(n_clusters = n_clusters).fit(X)

You just need:

df.loc[:,"cluster"] = kmeans.labels_