What you would learn in Data Visualization in Python - The Complete Package course?
This course will show you how to harness powerful Python to analyze data and create stunning visualizations.
In the opinion of LinkedIn, the Data Scientist position is the top job posted on LinkedIn and is among the top 100 most sought-after jobs. The median salary for Data Scientists is over $110,000, and data Scientist is over $110,000 in the United States and all over the World.
Visualization of data is the process of trying to understand data by putting it in a visual format so that patterns, examples, and connections that might not be detected are identified. Python has a range of charting libraries that are loaded with a variety of diverse components.
Here are just some of the subjects we'll be learning about:
Programming using Python
NumPy, in conjunction with Python
The Pandas Data Frames can be used to complete complicated tasks
Make use of Pandas to save files
Make use of matplotlib and Seaborn to visualize data
Utilize Plotly and Cufflinks to create interactive visualizations
Evaluative Data Analysis (EDA) of the Boston Housing Dataset
Evaluative Data Analysis (EDA) of Titanic Dataset
Evaluative Data Analysis (EDA) of the Covid-19 Dataset. dataset
and lots and more!
After this course, you'll:
Be aware of the programming language Python.
Learn how to make and manipulate arrays using NumPy programming language and Python.
Learn how to utilize pandas to design and analyze data sets.
Know how to utilize seaborn and matplotlib libraries to create stunning data visualization.
Have a stunning collection of Python analytical skills!
Experienced in making a visual representation of real-life projects
Content of the Course:
Create various charts such as Bar Charts and Line Charts, Stacked Charts, Pie Charts, Histograms, KDE plots, Violinplots Boxplots and Auto Correlation plots
Use the Pandas module in conjunction with Python to structure and create data.
Learn about Data Visualization using Plotly and Cufflinks Seaborn, matplotlib, and Pandas
Customize graphs and colors and alter the colors, lines, fonts, and more.
Use Data Visualization Concepts for Real-time Data Analysis and Interpretation
Additionally, you can join several different graphs into the form of a dashboard.
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