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!


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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()

Tarefa

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.

Tarefa

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.

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Tudo estava claro?

Seção 2. Capítulo 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()

Tarefa

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.

Tarefa

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.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Seção 2. Capítulo 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()

Tarefa

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.

Tarefa

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.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

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()

Tarefa

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.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Seção 2. Capítulo 6

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo