How can I plot a gaussian fit onto a histplot, as previously done by the deprecated distplot? import seaborn as sns import numpy as np from scipy.stats import norm x = np.random.normal(size=500) * ...

How can I retrieve arrays containing bin ranges and counts from a sns.displot()? I found older posts relating to the previous distplot() which do not seem to be applicable anymore.

I 'm using Seaborn in a Jupyter notebook to plot histograms like this: import numpy as np import pandas as pd from pandas import DataFrame import matplotlib.pyplot as plt import seaborn as sns %m...

How can each hue group of a seaborn.kdeplot, or seaborn.displot with kind='kde' be given a different linestyle? Both axes-level and figure-level options will accept a str for linestyle/ls, which ...

I am creating a histrogram (frecuency vs. count) and I want to add kernel density estimate line in a different colour. How can I do this? I want to change the colour for example sns.histplot(data=p...

distplot was deprecated in favour of displot. The previous function had the option to draw a normal curve. import seaborn as sns import matplotlib.pyplot as plt from scipy import stats ax = sns.di...

Histograms generated by seaborn.histplot and seaborn.displot do not match. Default plot for sns.displot is kind='hist' Tested with python3.8.11, seaborn 0.11.2, and matplotlib 3.4.2 Why do the ...

Is there a way to plot the percentage instead of the count on a distplot? ax = sns.FacetGrid(telcom, hue='Churn', palette=["teal", "crimson"], size=5, aspect=1) ax = ax.map(sns....

I want to plot histogram and kde line in the same plot with different color. I want to set green color for the histogram and blue color for the kde line. I managed to figure out using line_kws to c...

I have installed the latest version of seaborn (0.11.1). When I plot a hist with custom color, it show different color than I expected (see the color by sns.palplot). For some api, it has a saturat...

I have a dataframe which looks like below: df: RY MAJ_CAT Value 2016 Cause Unknown 0.00227 2016 Vegetation 0.04217 2016 Vegetation 0.04393 2016 Vegetation 0.07878 2016 Defective Equip 0.00137 201...