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

3-variable Lineplot

With the help of the seaborn, we can view the dynamics of the population, for example, relative to each season during 10 years by adding the third variable to our lineplot.

To initialize a lineplot based on the pandas DataFrame, you need to input at least 4 parameters: x, y (columns-markers for the plot), hue (the third variable), 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 the file
df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c5b4ea8f-8a30-439f-9625-ddf2effbd9ac/example5.csv')

# Creating the 3-variable lineplot
sns.lineplot(x = 'x', y = 'y', hue = 'gender', data=df)

# Showing the plot
plt.show()

Task

Swipe to show code editor

Import the seaborn with sns alias.
Import the matplotlib.pyplot with plt alias.
Import the pandas withpd alias.
Read the file using df variable.
Create a 3-variable lineplot using 'year' column for the x-value and 'population' column for the y-value and 'season' for the hue-value.
Show the plot.

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

Everything was clear?

Thanks for your feedback!

Section 2. Chapter 6

3-variable Lineplot

With the help of the seaborn, we can view the dynamics of the population, for example, relative to each season during 10 years by adding the third variable to our lineplot.

Look at the code below!


              12345678910111213
            
# Importing libraries needed
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd

# Reading the file
df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c5b4ea8f-8a30-439f-9625-ddf2effbd9ac/example5.csv')

# Creating the 3-variable lineplot
sns.lineplot(x = 'x', y = 'y', hue = 'gender', data=df)

# Showing the plot
plt.show()

Task

Swipe to show code editor

Import the seaborn with sns alias.
Import the matplotlib.pyplot with plt alias.
Import the pandas withpd alias.
Read the file using df variable.
Create a 3-variable lineplot using 'year' column for the x-value and 'population' column for the y-value and 'season' for the hue-value.
Show the plot.

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

Everything was clear?

Thanks for your feedback!

Section 2. Chapter 6

3-variable Lineplot

With the help of the seaborn, we can view the dynamics of the population, for example, relative to each season during 10 years by adding the third variable to our lineplot.

Look at the code below!


              12345678910111213
            
# Importing libraries needed
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd

# Reading the file
df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c5b4ea8f-8a30-439f-9625-ddf2effbd9ac/example5.csv')

# Creating the 3-variable lineplot
sns.lineplot(x = 'x', y = 'y', hue = 'gender', data=df)

# Showing the plot
plt.show()

Task

Swipe to show code editor

Import the seaborn with sns alias.
Import the matplotlib.pyplot with plt alias.
Import the pandas withpd alias.
Read the file using df variable.
Create a 3-variable lineplot using 'year' column for the x-value and 'population' column for the y-value and 'season' for the hue-value.
Show the plot.

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

Everything was clear?

Thanks for your feedback!

With the help of the seaborn, we can view the dynamics of the population, for example, relative to each season during 10 years by adding the third variable to our lineplot.

Look at the code below!


              12345678910111213
            
# Importing libraries needed
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd

# Reading the file
df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c5b4ea8f-8a30-439f-9625-ddf2effbd9ac/example5.csv')

# Creating the 3-variable lineplot
sns.lineplot(x = 'x', y = 'y', hue = 'gender', data=df)

# Showing the plot
plt.show()

Task

Swipe to show code editor

Import the seaborn with sns alias.
Import the matplotlib.pyplot with plt alias.
Import the pandas withpd alias.
Read the file using df variable.
Create a 3-variable lineplot using 'year' column for the x-value and 'population' column for the y-value and 'season' for the hue-value.
Show the plot.

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

Section 2. Chapter 6

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