Change colours on scatterplot

Question

Couldn't find an answer to my question.

I have the following code which generates the scatter plot below.

scatter_matrix(iris_ds) plt.show()

However, I can't seem to be able to change the colour of the points on the plots, in order to distinguish the data points.

Any suggestions?

Edit: for clarity - there are 3 sets of data points in each scatter plot box. I was wondering if there is a way to:

Change the colour from blue?
Change the colours depending on where on the plots the data points appear?

First and foremost, you should read How to create a Minimal, Complete, and Verifiable example. Next, you should clarify what points you mean when you say "in order to distinguish the data points.". There are 12 subplots with the scatter points — Sheldore
– Sheldore, Commented Apr 27, 2019 at 18:24
seaborn.pydata.org/examples/scatterplot_matrix.html concidentally, the exact same dataset, plotted in multiple colours. — warped
– warped, Commented Apr 27, 2019 at 18:47
@Clauric just curious, why can't you use sns? It fits your need in just one line of code. — Quang Hoang
– Quang Hoang, Commented Apr 27, 2019 at 20:55

warped · Accepted Answer · 2019-04-27 20:48:10Z

If you look at the source of pd.plotting.scatter_matrix:

def scatter_matrix(frame, alpha=0.5, figsize=None, ax=None, grid=False, diagonal='hist', marker='.', density_kwds=None, hist_kwds=None, range_padding=0.05, **kwds): # <--- [...] # Deal with the diagonal by drawing a histogram there. if diagonal == 'hist': ax.hist(values, **hist_kwds) # <--- [...] else: common = (mask[a] & mask[b]).values ax.scatter(df[b][common], df[a][common], marker=marker, alpha=alpha, **kwds) # <---

you see that the function takes **kwds and passes them to ax.scatter

so, you can either feed colors directly:

colors = iris['species'].replace({'setosa':'red', 'virginica': 'green', 'versicolor':'blue'}) pd.plotting.scatter_matrix(iris, c=colors);

or you convert the species to numbers, and use a colormap:

colors = iris['species'].replace({'setosa':1, 'virginica': 2, 'versicolor':3}) pd.plotting.scatter_matrix(iris, c=colors, cmap='viridis');

further, the function takes density_kwds and hist_kwds and passes them to ax.plot and ax.hist, respoectively. So, you can change the colour of the histograms by passing a dictionary. Ditto for the kdeplots:

pd.plotting.scatter_matrix(iris, hist_kwds={'color':'red'})

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