I want to plot a 3D matrix using the first column as the x coordinate, second as the y coordinate and the third column as the color.
So I tried it simply like this:
scat=np.matrix([[0,1,2],[10,11,12],[20,21,22]])
ax = sns.scatterplot(data=scat)
Buf for some strange reason instead of scatterplotting it, it plots it like a line plot on the x axis from left to right (from 0 to 2) for each row of data.
So how can I plot matrices how I described using seaborn
Do not use seaborn's scatterplot() if you are not using dataframes and if you don't need the functionality that it provides. Use matplotlib's scatter() directly instead.
PS: np.matrix seems to be deprecated, use np.array instead.
scat=np.array([[0,1,2],[10,11,12],[20,21,22]])
fig, ax = plt.subplots()
ax.scatter(np.squeeze(scat[:,0]), np.squeeze(scat[:,1]), c=np.squeeze(scat[:,2]))
cmap= parameter). See matplotlib.org/tutorials/colors/…does this works?
scat =np.array([[0,1,2],[10,11,12],[20,21,22]])
a =scat.T
a =pd.DataFrame({'x':a[0], 'y':a[1] , 'z':a[2]})
ax =sns.scatterplot(data=a, x='x', y='y', hue='z',palette="deep")
edit: you can use palette , you can refer https://seaborn.pydata.org/tutorial/color_palettes.html or https://chrisalbon.com/python/data_visualization/seaborn_color_palettes/
