Kmeans clustering using Clustering package

The documentation of kmeans of the Clustering.jl states that:

help?> kmeans
search: kmeans kmeans! kmeans_opts KmeansResult

  kmeans(X, k, [...]) -> KmeansResult

  K-means clustering of the d×n data matrix X (each column of X is a d-dimensional data point) into k clusters.

Does this mean rows of X represent the features and columns represent data samples?

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Thanks, Elias :orange_heart:

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