How do you make a diverging barchart in python

I'm trying to make a diverging barchart in python to show pathogenic mutations (represented as -1) and non-pathogenic mutations (represented as 1). Each appears at a certain position on the gene (1-250) and occurs a certain number of times per location (so you could have 8 occurring at position 24, 16 at 35 etc.).

I want the barchart to show pathogenic mutations going down and non-pathogenic going up, with x being position (1-250) and y being the count of each mutation at the given position, ergo the height of the bars corresponds to how many are at the position.

Does anyone have any ideas?

I want it to look a bit like this:

Dummy data:

import random
from random import choice
import pandas as pd

position = random.randint(1, 250)
pathogencity = choice([i for i in range(-1,1) if i not in 
[0]]))

df = pd.concat([pathogencity,position],axis=1) 

You can accomplish it like so:

Imports:

import matplotlib.pyplot as plt
import numpy as np

Dummy data:

N = 18 # Size of dummy data and graph, I took it based on your graph
positions = np.arange(1, N)
counts = np.random.randint(1, 20, size=N-1)
mut_types = np.random.choice([-1, 1], size=N-1)
# Splitting the data by mutation type
pos_counts = counts * (mut_types == 1)
neg_counts = counts * (mut_types == -1)

Method:

# Generating the bar chart
fig, ax = plt.subplots(figsize=(10, 6))
ax.bar(positions, pos_counts, color='green')
ax.bar(positions, -neg_counts, color='red')
# Setting the y-axis limits
max_y = max(abs(pos_counts).max(), abs(neg_counts).max())
ax.set_ylim(-max_y, max_y)
# Setting the x-axis limits and labels
ax.set_xlim(0, N)
ax.set_xticks(np.arange(0, N, 25))
ax.set_xlabel('Position')
ax.set_ylabel('Count')
ax.set_title('Mutation Counts by Position and Type')

plt.show()

Result:

Additional:

1. If you want to add a gridline, use ax.grid(visible= True, axis='both', linestyle='--', alpha=0.7, color='black', linewidth=1.5)

2. If you want to label only as Positive-Natural-Negative, in the top mid and bottom, you can use this y_ticks = ax.get_yticks() and then plt.yticks([min(y_ticks), 0, max(y_ticks)], ["Negative", "Natural", "Positive"])

I suppose you could do:

import matplotlib.pyplot as plt

# define data here
data = [-1, 2, 1, 5, -3]
x = range(1, len(data) + 1)

colors = ["green" if i > 0 else "red" for i in data]
plt.yticks([-2, 0, 2], ["negative", "neutral", "positive"])

plt.xlabel("Respondent")
plt.ylabel("Overall response sentiment")
plt.bar(x, data, color=colors)

plt.show()

Output:

Edit:
You can get the dashed x=0 line by adding:

plt.plot([0, x[-1] + 1], [0, 0], color="black", ls="--")

to your code.

New output: