Histplot
A histogram (aka histplot) is a classic visualization tool that represents the distribution of one or more variables by counting the number of observations that fall within discrete bins.
An example of a histplot:
To initialize a histplot based on the pandas
DataFrame, we need to input at least 2 parameters: x/y
(the column in which values will be used to create a histplot) 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 a file df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c5b4ea8f-8a30-439f-9625-ddf2effbd9ac/example6.csv') # Creating a histplot sns.histplot(x = 'value', data = df) # Showing the plot plt.show()
We can change the histogram binning intervals by using binwidth=n
as an argument in the plot function, n
- is the width of one column:
12345678910111213# Importing the libraries needed import seaborn as sns import matplotlib.pyplot as plt import pandas as pd # Reading a file df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c5b4ea8f-8a30-439f-9625-ddf2effbd9ac/example6.csv') # Creating a histplot sns.histplot(x = 'value', data = df, binwidth = 2) # Showing the plot plt.show()
Let's solve this problem!
Swipe to start coding
- Import the
seaborn
withsns
alias. - Import the
matplotlib.pyplot
withplt
alias. - Import the
pandas
withpd
alias. - Read the file using
df
variable. - Create a x-oriented lineplot using
'answer'
column in the plot function. - Set
binwidth = 0.2
. - Show the plot.
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Histplot
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A histogram (aka histplot) is a classic visualization tool that represents the distribution of one or more variables by counting the number of observations that fall within discrete bins.
An example of a histplot:
To initialize a histplot based on the pandas
DataFrame, we need to input at least 2 parameters: x/y
(the column in which values will be used to create a histplot) 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 a file df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c5b4ea8f-8a30-439f-9625-ddf2effbd9ac/example6.csv') # Creating a histplot sns.histplot(x = 'value', data = df) # Showing the plot plt.show()
We can change the histogram binning intervals by using binwidth=n
as an argument in the plot function, n
- is the width of one column:
12345678910111213# Importing the libraries needed import seaborn as sns import matplotlib.pyplot as plt import pandas as pd # Reading a file df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c5b4ea8f-8a30-439f-9625-ddf2effbd9ac/example6.csv') # Creating a histplot sns.histplot(x = 'value', data = df, binwidth = 2) # Showing the plot plt.show()
Let's solve this problem!
Swipe to start coding
- Import the
seaborn
withsns
alias. - Import the
matplotlib.pyplot
withplt
alias. - Import the
pandas
withpd
alias. - Read the file using
df
variable. - Create a x-oriented lineplot using
'answer'
column in the plot function. - Set
binwidth = 0.2
. - Show the plot.
Рішення
Дякуємо за ваш відгук!
Awesome!
Completion rate improved to 5.88single