Course Content
First Dive into seaborn Visualization
First Dive into seaborn Visualization
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()
Task
- Import the
seaborn
withsns
alias. - Import the
matplotlib.pyplot
withplt
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.
Thanks for your feedback!
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()
Task
- Import the
seaborn
withsns
alias. - Import the
matplotlib.pyplot
withplt
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.
Thanks for your feedback!
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()
Task
- Import the
seaborn
withsns
alias. - Import the
matplotlib.pyplot
withplt
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.
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!
# 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()
Task
- Import the
seaborn
withsns
alias. - Import the
matplotlib.pyplot
withplt
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.