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

Tarefa

  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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Tudo estava claro?

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Seção 2. Capítulo 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

Tarefa

  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 desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 2. Capítulo 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

Tarefa

  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 desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu 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

Tarefa

  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 desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Seção 2. Capítulo 6
Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
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