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Lære Histplot | More and More Plots
First Dive into seaborn Visualization

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Histplot

A histogram (aka 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.

An example of a histplot:

To initialize a histplot based on the pandas DataFrame, we need to input at least 2 parameters: x/y (the column in which values will be used to create a histplot) and data (the DataFrame containing the data).

Look at the code below!

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# Importing libraries needed import seaborn as sns import matplotlib.pyplot as plt import pandas as pd # Reading a file df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c5b4ea8f-8a30-439f-9625-ddf2effbd9ac/example6.csv') # Creating a histplot sns.histplot(x = 'value', data = df) # Showing the plot plt.show()
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We can change the histogram binning intervals by using binwidth=n as an argument in the plot function, n - is the width of one column:

12345678910111213
# Importing the libraries needed import seaborn as sns import matplotlib.pyplot as plt import pandas as pd # Reading a file df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c5b4ea8f-8a30-439f-9625-ddf2effbd9ac/example6.csv') # Creating a histplot sns.histplot(x = 'value', data = df, binwidth = 2) # Showing the plot plt.show()
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Let's solve this problem!

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Swipe to start coding

  1. Import the seaborn with sns alias.
  2. Import the matplotlib.pyplot with plt alias.
  3. Import the pandas with pd alias.
  4. Read the file using df variable.
  5. Create a x-oriented lineplot using 'answer' column in the plot function.
  6. Set binwidth = 0.2.
  7. Show the plot.

Løsning

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book
Histplot

A histogram (aka 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.

An example of a histplot:

To initialize a histplot based on the pandas DataFrame, we need to input at least 2 parameters: x/y (the column in which values will be used to create a histplot) and data (the DataFrame containing the data).

Look at the code below!

12345678910111213
# Importing libraries needed import seaborn as sns import matplotlib.pyplot as plt import pandas as pd # Reading a file df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c5b4ea8f-8a30-439f-9625-ddf2effbd9ac/example6.csv') # Creating a histplot sns.histplot(x = 'value', data = df) # Showing the plot plt.show()
copy

We can change the histogram binning intervals by using binwidth=n as an argument in the plot function, n - is the width of one column:

12345678910111213
# Importing the libraries needed import seaborn as sns import matplotlib.pyplot as plt import pandas as pd # Reading a file df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c5b4ea8f-8a30-439f-9625-ddf2effbd9ac/example6.csv') # Creating a histplot sns.histplot(x = 'value', data = df, binwidth = 2) # Showing the plot plt.show()
copy

Let's solve this problem!

Oppgave

Swipe to start coding

  1. Import the seaborn with sns alias.
  2. Import the matplotlib.pyplot with plt alias.
  3. Import the pandas with pd alias.
  4. Read the file using df variable.
  5. Create a x-oriented lineplot using 'answer' column in the plot function.
  6. Set binwidth = 0.2.
  7. Show the plot.

Løsning

Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

close

Awesome!

Completion rate improved to 5.88

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