Learn 3-variable Lineplot | More and More Plots

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 start coding

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.

Solution

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

single

Ask AI

Ask anything or try one of the suggested questions to begin our chat

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 start coding

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.

Solution

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

single

Swipe to show menu

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 start coding

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.

Solution

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

Everything was clear?

Thanks for your feedback!

3-variable Lineplot

Solution

Awesome!

3-variable Lineplot

Solution

Awesome!

3-variable Lineplot

Solution