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customize seaborn plot

Innocent Iguana answered on November 13, 2023 Popularity 1/10 Helpfulness 8/10

answer customize seaborn plot

related seaborn plot customization

customize seaborn plot

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import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt

# Create containers for Subplots
fig, (ax0, ax1) = plt.subplots(nrows=1, ncols=2,
sharey=True, figsize=(7,4))
# Put plots into containers
sns.histplot(df['col1'], stat='density', ax=ax0)
sns.histplot(df['col2'], stat='density', ax=ax1)
ax1.set(xlabel="X axis label", ylabel="Y axis label", xlim=(0, 50000),
    title="Some title")
ax1.axvline(x=20000, label='Vertical legend', linestyle='--')
ax1.legend()

Popularity 1/10 Helpfulness 8/10 Language python

Source: Grepper

Tags: plot python seaborn

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Contributed on Nov 14 2023

Innocent Iguana

0 Answers Avg Quality 2/10

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seaborn plot customization

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import seaborn as sns
g = sns.(yourplot)

# See what type of plot object it is
print(type(g))

# if g is FacetGrid object (it has the ability to create subplots)
# Add title to plot
g.fig.suptitle("Title", y=1.03)
# Add title to subplots
g.set_titles("This is {col_name}") # Make sure col attribute is defined in g

# if g is AxesSubplot object (it has the ability to create single plot)
# Add title to plot
g.set_title("Title", y=1.03)

# Add axis labels
g.set(xlabel="New X Label", ylabel="New Y Label")
# Rotate axis ticks
plt.xticks(rotation=90)

Popularity 4/10 Helpfulness 7/10 Language python

Source: Grepper

Tags: customization python plot seaborn

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Contributed on Nov 13 2023

Innocent Iguana

0 Answers Avg Quality 2/10

customize seaborn plot

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