Udemy - Ultimate Seaborn Data Visualization with Python's Seaborn

Category: Tutorial

Posted on 2021-11-18, by voska89.


MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 34 lectures (6h 49m) | Size: 1.59 GB
High-impact data visualizations in under two lines of code

What you'll learn:
Ask the right questions about the data using summary statistics and Visual Exploratory Data analysis to gain accelerated insight into the data
Generate distribution, categorical, relational and regression Descriptions to learn more about the variables in the dataset
Display maximum information using not only color, size and shape, but the power of multiples
Leverage the power of multiples, and apply aesthetic abilities functionally for effective data storytelling
Develop an intuition behind some automated visualization libraries like Autoviz to replicate the workflow for your own dataset
Basics of Python - an introduction to the Pandas library is included. However Seaborn is easy to learn because of its high level interface.
Curiosity and an interest in exploratory data analysis
Seaborn is the perfect library for a beginner in Data Science
Reason 1: High-level Descriptionting interface
Seaborn is a high-level Descriptionting interface which simplifies Descriptionting capabilities for beginners to data visualization greatly. The Python Seaborn library is often learn AFTER a user has studied MatDescriptionlib. However, learning Seaborn first instead could greatly accelerate the development of an intuition in working with different types of data since the bulk of constructing a Description has been integrated into Seaborn's high-level Descriptionting interface.
Also Seaborn has opinionated defaults which uses semantic tenets like color, size and style to communicate information - functional as opposed to purely aesthetic. Seaborn does this by inferring the datatype and then making choices: such as choosing the right color palette to display numerical information or categorical information.
Reason 2: Wide and long-form dataframes
Seaborn can be easily used for both wide and long form dataframes. The course contains a portion on transforming data from wide to long-form data to better leverage Seaborn's Descriptionting functionalities using Pandas.
Reason 3: Inbuilt datasets
Seaborn's inbuilt datasets like the Tips dataset, the Iris and Penguins datasets contain a mix of categorical and continuous numerical variables allowing for an exploration of the distribution, categorical, regression and relational Descriptions, together with the Descriptionting of multiples and facet Descriptions. A level of familiarity with the datasets (and a commitment to explore and practice with different datasets) will accelerate the development of an intuition on how best to navigate a previously unseen dataset.
Reason 4: Aesthetically pleasing production quality Descriptions
Seaborn's Descriptions are built to be aesthetically pleasing through the use of its color palettes, themes, styles etc. Seaborn is the library where a complete beginner can begin producing production-ready Descriptions almost immediately after completion of the course.
The course contains a combination of code walkthroughs which show the user how to enhance a Description + high-level thinking and an intuition to convey relevant information, depending on the decision-maker and stakeholders and the purpose of the visualization.
The course is delivered on Google Colab and uses a range of inbuilt datasets from Seaborn. The course also includes a presentation on Autoviz, an automated data visualization library to introduce the learner to the process through which visualization can be entirely automated.
Who this course is for
For anyone looking to elevate their data visualization abilities with just a few lines of code to produce attractive visualizations
Python developers looking to gain fluency with a visualization library
Anyone looking to learn the basics of statistical data visualization
Data storytellers looking to expand to using Seaborn for its high-level interface allowing one to Description attractive, information-rich Descriptions with just a few lines of code
Data analysts looking to learn and apply visual exploratory data analysis
For rapid prototyping and exploration

f472b4843daac9b0069c54c4b030364c.png More Course Expensive Download Click Here : https://www.ebookee.com/user/voska89


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