Lære 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!


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# 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()

Opgave

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.

Løsning

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Sektion 2. Kapitel 6

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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()

Opgave

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.

Løsning

Skift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder

Var alt klart?

Tak for dine kommentarer!

Sektion 2. Kapitel 6

single

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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()

Opgave

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.

Løsning

Skift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder

Var alt klart?

Tak for dine kommentarer!

3-variable Lineplot

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Awesome!

3-variable Lineplot

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Awesome!

3-variable Lineplot

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