Visualizing Pandas DF using numpy

Question

I have a 50 x 300 pandas data frame titled embeddings and would like to view it as a numpy array. I am using the function view_samples below:

def view_samples(samples, m, n): 
    fig, axes = plt.subplots(figsize=(10, 10), nrows=m, ncols=n, sharey=True, sharex=True) 
    for ax, img in zip(axes.flatten(), samples): 
        ax.xaxis.set_visible(False) 
        ax.yaxis.set_visible(False) 
        im = ax.imshow(1-img.reshape((50,300)), cmap='Greys_r') 
    return fig, axes

And running it as follows:

faces = [embeddings.to_numpy()]
_ = view_samples(faces, 1, 4)

The current result is shown below. Only the first one (leftmost) is correct, the other pictures are not.

current error output

Given the error, I am also trying to rewrite the function such that I do not include subplots, i.e. just the leftmost one.

Quang Hoang · Accepted Answer · 2020-12-12 04:13:20Z

1

The problem is here:

faces = [embeddings.to_numpy()]

That is len(faces)==1. So with:

for ax, img in zip(axes.flatten(), samples):

you only get to draw once. Maybe you mean:

faces = embeddings.to_numpy()

answered Dec 12, 2020 at 4:13

Quang Hoang

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3 Comments

ablam Over a year ago

I actually get len(faces)==50, and when I use faces = embeddings.to_numpy() : cannot reshape array of size 300 into shape (50,300) so I changed it to (10,30) and it worked!

Quang Hoang Over a year ago

If you only have one face, why would you expect 4 plots?

ablam Over a year ago

I rewrote it to expect one plot. I was trying to achieve that in the end goal.

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