EDUCBA

EDUCBA

MENUMENU
  • Free Tutorials
  • Free Courses
  • Certification Courses
  • 360+ Courses All in One Bundle
  • Login
Home Data Science Data Science Tutorials Seaborn Tutorial Seaborn Time Series
Secondary Sidebar
Seaborn Tutorial
  • Seaborn Basic and Advanced
    • Seaborn
    • Seaborn Histogram
    • Seaborn heatmap
    • Seaborn barplot
    • Seaborn Scatter Plot
    • Seaborn Countplot
    • Seaborn regplot
    • Seaborn Catplot
    • Seaborn Legend
    • Seaborn jointplot
    • Seaborn Figure Size
    • Seaborn Time Series
    • Seaborn Heatmap Size
    • Seaborn Graphs
    • Seaborn Palette
    • Seaborn Subplots
    • Seaborn Line Plot
    • Seaborn Pairplot
    • Seaborn Boxplot
    • Seaborn Color Palette
    • Seaborn Violin Plot
    • Seaborn Styles
    • Seaborn Implot
    • Seaborn Kdeplot
    • Seaborn Multiple Plots
    • Seaborn Distribution Plot
    • Seaborn Bar Chart
    • Seaborn 3D Plot
    • Seaborn Stacked Bar Plot
    • Seaborn Datasets
    • Seaborn Correlation Heatmap

Seaborn Time Series

Seaborn Time Series

Introduction to Seaborn Time Series

Seaborn time series is a special data type where we observe the set of operations per time. We are recording the timestamp of every observation. This data type is dealt with when discussing application monitor data and stock prices. For plotting the time series graph using seaborn, we need to set the figure size and adjust the padding between multiple subplots.

Key Takeaways

  • The seaborn ts plot is a new addition to a recent module version. It is used when we have timestamp data available for it.
  • This function plots the time series data, either in a data frame or an N-dimensional array.

Overview of Seaborn Time Series

It is nothing but the type of data in which we can set the measurement; every observation contains its timestamp. The time plot shows values changing as per time, like the x and y graphs. The time plot is only representing the time of an x-axis. The x and y graphs only plot the x variables such as age, weight, and height.

This plot is not including categories like bar or pie charts. Time series plots are helpful to display the progression of the data as per time. This chart type is proper if we analyze the data as per odd intervals. Suppose we plot the time plots using the panda module; pandas are nothing but the open source library based on numpy. The python module provides multiple data structures and methods for processing the statistical data. It is well known for making the analysis and data import more easily.

How to Use Seaborn Time Series?

While using it, we need to follow the below steps as follows. Also, we need to install and import the seaborn module in our code.

Start Your Free Data Science Course

Hadoop, Data Science, Statistics & others

  • First, we must download and install the seaborn and matplotlib module in our system.
  • After installing the module, we must import the same using the import keyword.
  • After importing the module, we need to set the figure size and add the padding between multiple plots.
  • After setting the figure size, we create the panda’s data frame for holding the date time series.
  • After creating the panda’s data frame, we are making the seaborn line plot using the data.
  • In the last step, we rotate the params by 45, and then we display the graph figure using the show method.

The below example shows how we can use the seaborn time series in the plot as follows. We are importing the seaborn, pandas, matplotlib, and numpy modules in the example below.

Code:

import seaborn as sns
from matplotlib import pyplot as plt
import pandas as pd
import numpy as np
plt.rcParams["figure.figsize"] = [5, 3]
plt.rcParams["figure.autolayout"] = True
plot = pd.DataFrame(
dict (
plot_time = list (pd.date_range ("2022-08-01 11:00:00", periods = 12, freq = "60min")),
plot_speed = np.linspace (1, 12, 12) ) )
ax = sns.lineplot (x = "plot_time", y = "plot_speed", data = plot)
ax.tick_params (rotation = 60)
plt.show()

Output:

Seaborn Time Series 1

In below example we are using multiple data with plot data as follows. We are importing the seaborn library.

Code:

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
plot = pd.DataFrame ({"plot_date": ['05/03/2022', '10/02/2022', '19/04/2022', '24/07/2022'],
"plot_no": [47, 36, 68, 20]})
plt.figure (figsize = (5, 7))
sns.lineplot (x = 'plot_date', y = 'plot_no', data = plot)
plt.show ()

Output:

multiple data

Seaborn Time Series Plots

The plot is used to visualize the data values which was changing as per time. Below example shows plot single time series as follows:

Code:

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
plot = pd.DataFrame ({"plot_date": ['10/05/2021', '15/05/2021', '20/05/2021', '25/05/2021'],
"plot_no": [37, 56, 78, 60]})
plt.figure (figsize = (5, 7))
sns.lineplot (x = 'plot_date', y = 'plot_no', data = plot)
plt.show()

Output:

visualize the data values which was changing

In below example we are customizing the color of a graph, we are adding color as red and defining the linewidths and line styles as follows.

All in One Data Science Bundle(360+ Courses, 50+ projects)
Python TutorialMachine LearningAWSArtificial Intelligence
TableauR ProgrammingPowerBIDeep Learning
Price
View Courses
360+ Online Courses | 50+ projects | 1500+ Hours | Verifiable Certificates | Lifetime Access
4.7 (86,471 ratings)

Code:

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
plot = pd.DataFrame ({"plot_date": ['10/05/2021', '15/05/2021', '20/05/2021', '25/05/2021'],
"plot_no": [37, 56, 78, 60]})
plt.figure (figsize = (5, 7))
sns.lineplot (x = 'plot_date', y = 'plot_no', data = plot, linewidth = 4, color = 'red', linestyle = 'dashed')
plt.show ()

Output:

we are customizing the color of a graph

In the following plot, we are plotting the multiple time series as follows. We are using hue parameter for the same.

Code:

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
plot = pd.DataFrame ({"plot_date": ['10/05/2021', '15/05/2021', '20/05/2021', '25/05/2021'],
  "plot_no": [37, 56, 78, 60], "plot_no1": ['P', 'P', 'R', 'R']})
plt.figure (figsize = (5, 7))
sns.lineplot (x = 'plot_date', y = 'plot_no', hue = 'plot_no1', data = plot, linewidth = 4, color = 'red', )
plt.show ()

Output:

Seaborn Time Series 5

Examples of Seaborn Time Series

Given below are the examples mentioned:

Example #1

In the below example, we are plotting single time series as follows.

Code:

import seaborn as sns
from matplotlib import pyplot as plt
import pandas as pd
import numpy as np
plt.rcParams ["figure.figsize"] = [5, 3]
plt.rcParams ["figure.autolayout"] = True
time_plot = pd.DataFrame (
dict (
plot_time = list (pd.date_range ("2022-08-05 10:00:00", periods = 8, freq = "45min")),
plot_speed = np.linspace (1, 8, 8) ) )
ax = sns.lineplot (x = "plot_time", y = "plot_speed", data = time_plot)
ax.tick_params (rotation = 60)
plt.show ()

Output:

Seaborn Time Series 6

Example #2

In the below example, we are plotting two-time series on a single plot as follows. We are using two series.

Code:

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
plot = pd.DataFrame ({"plot_date": ['10/010/2021', '15/10/2021', '20/10/2021', '25/10/2021'],
  "stud_marks": [37, 56, 78, 60],
  "stud_name": ['ABC', 'PQR', 'XYZ', 'MNP']})
plt.figure (figsize = (3, 3))
sns.lineplot (x = 'plot_date', y = 'stud_marks', hue = 'stud_name', data = plot, linewidth = 4, color = 'green', )
plt.show ()

Output:

Seaborn Time Series 7

FAQ

Given below are the FAQs mentioned:

Q1. What is the use of seaborn time series in python?

Answer:

The data type is used to plot the time series graph by using seaborn and matplotlib libraries.

Q2. Which libraries do we need to use at the time of plotting the graph?

Answer:

We need to use the seaborn, matplotlib, numpy, and pandas library at the time of plotting the graph.

Q3. What is the time plot in seaborn time series?

Answer:

The time plot in seaborn will display the values which were against the clock. It is like x and y graphs but it will displays x axis.

Conclusion

It is nothing but the type of data in which we can set the measurement, every observation contains its timestamp. It is a special data type where we are observing the set of operations as per time. We are recording the timestamp of every observation.

Recommended Articles

This is a guide to Seaborn Time Series. Here we discuss the introduction, how to use seaborn time series? examples and FAQ respectively. You may also have a look at the following articles to learn more –

  1. Seaborn barplot
  2. Seaborn heatmap
  3. Seaborn Scatter Plot
  4. Seaborn Histogram
Popular Course in this category
Seaborn Tutorial (3 Courses, 2+ Projects)
  3 Online Courses |  2 Hands-on Project |  8+ Hours |  Verifiable Certificate of Completion
4.5
Price

View Course
0 Shares
Share
Tweet
Share
Primary Sidebar
Footer
About Us
  • Blog
  • Who is EDUCBA?
  • Sign Up
  • Live Classes
  • Corporate Training
  • Certificate from Top Institutions
  • Contact Us
  • Verifiable Certificate
  • Reviews
  • Terms and Conditions
  • Privacy Policy
  •  
Apps
  • iPhone & iPad
  • Android
Resources
  • Free Courses
  • Database Management
  • Machine Learning
  • All Tutorials
Certification Courses
  • All Courses
  • Data Science Course - All in One Bundle
  • Machine Learning Course
  • Hadoop Certification Training
  • Cloud Computing Training Course
  • R Programming Course
  • AWS Training Course
  • SAS Training Course

ISO 10004:2018 & ISO 9001:2015 Certified

© 2022 - EDUCBA. ALL RIGHTS RESERVED. THE CERTIFICATION NAMES ARE THE TRADEMARKS OF THEIR RESPECTIVE OWNERS.

EDUCBA
Free Data Science Course

SPSS, Data visualization with Python, Matplotlib Library, Seaborn Package

*Please provide your correct email id. Login details for this Free course will be emailed to you

By signing up, you agree to our Terms of Use and Privacy Policy.

EDUCBA Login

Forgot Password?

By signing up, you agree to our Terms of Use and Privacy Policy.

EDUCBA
Free Data Science Course

Hadoop, Data Science, Statistics & others

*Please provide your correct email id. Login details for this Free course will be emailed to you

By signing up, you agree to our Terms of Use and Privacy Policy.

EDUCBA

*Please provide your correct email id. Login details for this Free course will be emailed to you

By signing up, you agree to our Terms of Use and Privacy Policy.

Let’s Get Started

By signing up, you agree to our Terms of Use and Privacy Policy.

This website or its third-party tools use cookies, which are necessary to its functioning and required to achieve the purposes illustrated in the cookie policy. By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to our Privacy Policy

Loading . . .
Quiz
Question:

Answer:

Quiz Result
Total QuestionsCorrect AnswersWrong AnswersPercentage

Explore 1000+ varieties of Mock tests View more