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3-variable Lineplot | More and More Plots
First Dive into seaborn Visualization

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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!

# 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()
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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()
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Tarefa
test

Swipe to show code editor

  1. Import the seaborn with sns alias.
  2. Import the matplotlib.pyplot with plt alias.
  3. Import the pandas withpd alias.
  4. Read the file using df variable.
  5. 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.
  6. Show the plot.

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Seção 2. Capítulo 6
# Import libraries needed
___
___
___

# Read the file
___ = ___.___('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c5b4ea8f-8a30-439f-9625-ddf2effbd9ac/lineplothue.csv')

# Create a lineplot
___.___(___ = '___', ___ = '___', ___ = '___', ___)

# Showing the plot
plt.show()
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