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

Course Content

First Dive into seaborn Visualization

First Dive into seaborn Visualization

1. Nice to Meet you, seaborn!
2. More and More Plots
3. Plot Customization

book3-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()
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Task

  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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Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 2. Chapter 6
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book3-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()
copy

Task

  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.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 2. Chapter 6
toggle bottom row

book3-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()
copy

Task

  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.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

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.

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()
copy

Task

  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.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 2. Chapter 6
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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