matplotlib visualization- positive negative proportion chart

Question

I'm trying to make the same chart as below and wonder if matplotlib has a similar chart to make that.

The chart below is the result of the STM topic model in the R package

I have probs values using DMR in Python:

array([[0.07204196, 0.04238116],
       [0.04518877, 0.30546978],
       [0.0587892 , 0.19870868],
       [0.16710107, 0.07182639],
       [0.128209  , 0.02422131],
       [0.15264449, 0.07237352],
       [0.2250081 , 0.06986096],
       [0.1337716 , 0.10750801],
       [0.01197221, 0.06736039],
       [0.00527367, 0.04028973]], dtype=float32)

These are the results and left is Negative words and right is Positive

Example of negative positive proportion chart:

Answer 1

It is possible to create something quite close to the image you included. I understood that the right column should be negative while the right column should be positive?

First make the data negative:

import numpy as np

arr = np.array([[0.07204196, 0.04238116],
                [0.04518877, 0.30546978],
                [0.0587892 , 0.19870868],
                [0.16710107, 0.07182639],
                [0.128209  , 0.02422131],
                [0.15264449, 0.07237352],
                [0.2250081 , 0.06986096],
                [0.1337716 , 0.10750801],
                [0.01197221, 0.06736039],
                [0.00527367, 0.04028973]], dtype="float32")

# Make the right col negative
arr[:, 0] *= -1

Then we can plot like so:

from string import ascii_lowercase
import matplotlib.pyplot as plt


fig, ax = plt.subplots()

for y, x in enumerate(arr.flatten()):
    # Get a label from the alphabet
    label = ascii_lowercase[y]
    # Plot the point
    ax.plot(x, y, "o", color="black")
    # Annotate the point with the label
    ax.annotate(label, xy=(x, y), xytext=(x - 0.036, y), verticalalignment="center")

# Add the vertical line at zero
ax.axvline(0, ls="--", color="black", lw=1.25)

# Make the x axis equal
xlim = abs(max(ax.get_xlim(), key=abs))
ax.set_xlim((-xlim, xlim))

# Remove y axis
ax.yaxis.set_visible(False)

# Add two text labels for the x axis
for text, x in zip(["Negative", "Positive"], ax.get_xlim()):
    ax.text(x / 2, -3.75, f"{text} Reviews", horizontalalignment="center")

Which outputs:

You can tweak the values in the calls to ax.annotate and ax.text if you need to change the locations of the text on the plot or x-axis.