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First Dive into seaborn Visualization

bookHistplot

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!

Task

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.

Solution

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Thanks for your feedback!

SectionΒ 2. ChapterΒ 7
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bookHistplot

Swipe to show menu

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!

Task

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.

Solution

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Everything was clear?

How can we improve it?

Thanks for your feedback!

SectionΒ 2. ChapterΒ 7
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