How can I create a density plot (using as a reference a histogram) [duplicate]

Question

I have the following script

import matplotlib.pyplot as plt
import numpy as np

fig5 = plt.figure()
fig5.subplots_adjust(wspace=0.4, hspace=0.6)
ax5_2 = fig5.add_subplot(212)
std_error = "{:.2f}".format(np.std(df['error']))
ave_error = "{:.2f}".format(np.nanmean(df['error']))
ax5_2.set_title("Error Histogram ave:" + ave_error + " std:" + std_error)
ax5_2.hist(df['error'], range=(0, 2), bins=20)

with that I get

I want to plot the density here. I tried

hist,bin_edges=np.histogram(df['error'], range=(0, 2), bins=20,density=True)
bin_widths=np.diff(bin_edges)
densities = hist / (np.sum(hist) * bin_widths)
plt.bar(bin_edges[:-1], densities, width=bin_widths, align='edge')

# Customize your plot as needed
plt.xlabel('X-axis Label')
plt.ylabel('Density')
plt.title('Density Plot')

with that I got

Is this correct? And second, I thought density plots were smooth line-like plots and not bars.

How can I create the density plot corresponding to the histogram above?

(I tried seaborn completely unrelated histograms and density plots...)

EDIT: I tried mcgusty solution

errors = np.random.randn(100)
df = pd.DataFrame({'errors': errors})
sns.histplot(data=df, x="errors", kde=True)

and I got

but then I tried the equivalent in matplotlib

fig5 = plt.figure()
fig5.subplots_adjust(wspace=0.4, hspace=0.6)
ax5_2 = fig5.add_subplot(212)
ax5_2.hist(errors, range=(-3, 3), bins=9)

and I got and

hist,bin_edges=np.histogram(errors, range=(-3, 3), bins=9,density=True)
bin_widths=np.diff(bin_edges)
densities = hist / (np.sum(hist) * bin_widths)
plt.bar(bin_edges[:-1], densities, width=bin_widths, align='edge')

Quite different!

sns.histplot(data=errors, bins=10, kde=True) produces the same histogram bars as plt.hist(errors, bins=10, ec='k'). If you want density in seaborn, you have to specify that, sns.histplot(data=errors, bins=10, kde=True, stat='density'). — Trenton McKinney
– Trenton McKinney, Commented Oct 2, 2023 at 15:40
@TrentonMcKinney I did what you indicated. Yes sns produced the same histogram as plt, and then I could get the density with sns. The final question is, how can I get this same last density with plt? — KansaiRobot
– KansaiRobot, Commented Oct 3, 2023 at 0:32
If you look at plt.hist, you'll see that it has a Boolean density parameter. The docs show the relevant calculation that's used. The duplicate shows how to calculate the curve. — Trenton McKinney
– Trenton McKinney, Commented Oct 3, 2023 at 1:07

arunppsg · Accepted Answer · 2023-10-02 12:51:43Z

0

I think using seaborn.histplot can help in adding a density-plot over the bars.

Something like this should probably work:

import numpy as np
import pandas as pd
import seaborn as sns

errors = np.random.randn(100)
df = pd.DataFrame({'errors': errors})
sns.histplot(data=df, x="errors", kde=True)

answered Oct 2, 2023 at 12:51

arunppsg

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1 Comment

KansaiRobot Over a year ago

I tried your solution but the results were quite different (see EDIT)

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