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First Dive into seaborn Visualization
course content

Course Content

First Dive into seaborn Visualization

First Dive into seaborn Visualization

1. Nice to Meet you, seaborn!
Practical ApplicationA Little about seabornCountplotSeaborn + Pandas
2. More and More Plots
Do you Need more Plots?Scatterplot3-variable ScatterplotColors in a 3-variable PlotLineplot3-variable LineplotHistplot
3. Plot Customization
Why do we Need to Customize?Adding the Plot TitleLet's Cope with AxesDecoration and...Decoration!I'm an Artist, that's how I See it!Final Challenge

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
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

  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.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 2. Chapter 7
toggle bottom row

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
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

  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.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 2. Chapter 7
toggle bottom row

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
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

  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.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

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
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

  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.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 2. Chapter 7
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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