Histplot
The distributions module contains several functions designed to answer questions such as these. The axes-level functions are histplot, kdeplot, ecdfplot, and rugplot. They are grouped together within the figure-level displot function.
A histplot is a classic visualization tool that represents the distribution of one or more variables by counting the number of observations that fall within discrete bins.
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Note
Use
plt.show()to display the plot.
Taak
Swipe to start coding
- Create the histplot using the
seabornlibrary:
- Set the
xparameter equals the'bill_length_mm'; - Set the
hueparameter equals the'island'; - Set the
elementparameter equals the'step'; - Set the
statparameter equals the'density'; - Set the
binwidthparameter equals1; - Set the
'flare'palette; - Use the
dfdata for the plot; - Display the plot.
Oplossing
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import warnings
# Ignore all warnings
warnings.filterwarnings('ignore')
# Importing libraries needed
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
# Reading the file
df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/66ba0c8e-8422-413c-b7e1-74bd24c61656/penguins.csv')
# Create a histplot
sns.histplot(# Set the x
x = 'bill_length_mm',
# Set the hue
hue = 'island',
# Set the element
element = 'step',
# Set the stat
stat = 'density',
# Set the binwidth
binwidth = 1,
# Set the palette
palette = 'flare',
# Set the data
data = df)
# Display the plot
plt.show()
Was alles duidelijk?
Bedankt voor je feedback!
Sectie 2. Hoofdstuk 1
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import warnings
# Ignore all warnings
warnings.filterwarnings('ignore')
# Importing libraries needed
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
# Reading the file
df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/66ba0c8e-8422-413c-b7e1-74bd24c61656/penguins.csv')
# Create a histplot
sns.___(# Set the x
x = '___',
# Set the hue
hue = '___',
# Set the element
element = '___',
# Set the stat
stat = '___',
# Set the binwidth
___ = 1,
# Set the palette
___ = '___',
# Set the data
data = ___)
# Display the plot
___
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