How to draw a scatter plot using Seaborn in Python
A scatter plot displays data between two continuous data. It shows how one data variable affects the other variable. A scatter plot can display data in different types of plots, both 2D and 3D.
Seaborn is a widely-used library in Python for data visualization. It represents data in a straightforward way in the form of plots.
Seaborn offers different ways of styling the plots, such as by changing the color palette with multiple options. In Seaborn, we use the scatterplot() method to create plots.
Syntax
sns.scatterplot(x, y, data)
sns: It is the Seaborn variable.
Parameters
x: It is the data value on the x-axis.y: It is the data value on the y-axis.data: It is a DataFrame containing variables and observations.
Return value
Code
In the code snippet below, we visualize a data frame in pictorial form:
import pandas as pdimport seaborn as snsimport matplotlib.pyplot as plt# A list containing year valuesYear = [2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016]# A list containing profit valuesProfit = [90, 65.8, 74, 65, 99.5, 19,33.6,23,35,12,86,34,867,20,70,64,44]# pd.DataFrame converts lists to a dataframedata_plot = pd.DataFrame({"Year":Year, "Profit":Profit})# the scatterplot function represent data in the form of dotssns.scatterplot(x = "Year", y = "Profit", data= data_plot)
Code explanation
- Line 5: We create a list named
Yearto include the years. - Line 8: We create a list named
Profitto include the profit figures. - Line 11: We create a data frame with
Yearas the x-axis label andProfitas the y-axis label. - Line 13: We invoke the
sns.scatterplot()function from the Seaborn library to generate a scatter plot on the data above.
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