Seaborn automatically scaling Y axis

Question

I am using Seaborn to plot some data.

The problem I am facing is that Y-axis is automatically getting scaled and not showing actual numbers.

survive_count = sns.barplot(x="Pclass", y='Survived', data=df)

What can be the possible solution to eliminate this?

After few suggestions, I tried

survive_count = sns.countplot(x="Pclass", hue='Survived', data=df)
survive_count.figure.savefig(my_path + '/Class vs Survival Count.png')

But, unfortunately, I landed up on another problem

I am really confused why I am having this inverted image.

To solve this, I tried

plt.gca().invert_yaxis()

and

plt.ylim(reversed(plt.ylim()))

But both solutions did not work.

Answer 1

You might want to use a countplot. By default, a barplot averages out the values.

import seaborn as sns
import matplotlib.pyplot as plt

df = sns.load_dataset('titanic')
ax = sns.countplot(x="pclass", data=df[df['survived'] == 1])
plt.show()

Or using hue:

sns.set_theme("paper")
df = sns.load_dataset('titanic')
ax = sns.countplot(x="pclass", hue="survived", data=df)

Answer 2

the reason I guess is that seaborns bar plot do the mean value of the category. Please see if any of the code below helps you.

survive_count = sns.barplot(x="Pclass", y='Survived', data=df, estimator=sum)

survive_count = sns.barplot(x="Pclass", y='Survived', data=df, estimator=len)

from numpy import count_nonzero
survive_count = sns.barplot(x="Pclass", y='Survived', data=df, estimator= count_nonzero)