Course Content

First Dive into seaborn Visualization

1. Nice to Meet you, seaborn!

Practical Application A Little about seaborn Countplot Seaborn + Pandas

2. More and More Plots

Do you Need more Plots?Scatterplot 3-variable Scatterplot Colors in a 3-variable Plot Lineplot 3-variable Lineplot Histplot

3. Plot Customization

Why do we Need to Customize?Adding the Plot Title Let's Cope with Axes Decoration and...Decoration!I'm an Artist, that's how I See it!Final Challenge

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()

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
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()

Let's solve this problem!

Task

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

Task

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

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Section 2. Chapter 7

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:

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()

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
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()

Let's solve this problem!

Task

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

Task

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

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Section 2. Chapter 7

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:

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()

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
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()

Let's solve this problem!

Task

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

Task

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

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

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:

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()

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
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()

Let's solve this problem!

Task

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

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Section 2. Chapter 7

Switch to desktop for real-world practiceContinue from where you are using one of the options below