Learn Data Visualization with Python, Plotly, and Power BI – Free Udemy Courses
Learn to build interactive charts with Plotly and Power BI asap
What you’ll learn
Learn Data Visualization with Python, Plotly, and Power BI – Free Udemy Courses
- Learn to create interactive charts with Plotly
- Learn to build dummy datasets like Fake Stock market price simulator
- Learn to create vertical and horizontal bar charts
- Learn to create vertical and horizontal grouped and stacked bar charts
- Learn to create scatter charts
- Learn to create line charts
- Learn to create time series charts
- Learn to create pie, donut, and sunburst charts
- Learn to create multiple line charts
- Learn to create a bubble and dot charts
Requirements
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A desire to transform complicated data into beautiful charts
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A little bit of knowledge of python programming language
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Must have Jupyter and other required packages and libraries
Description
In this course, you will learn to create various types of Data Visualization charts using Microsoft Power BI, Python, and Plotly. There is a wide range of professionals who require data visualization skills to plot various charts to find critical insights from the dataset. From Marketing and sales professionals to Developers, Analysts, and Data Scientists, a large number of professionals require some kind of knowledge to adequately model and represent data in creative visuals that makes it easy and intuitive to understand the complex data value in form for comparable and easy-to-understand visual charts.
Most of the basic charts such as bar, line, pie, tree maps, and other charts in Power BI and other visualization software are just inefficient to represent various kinds of data with complex information. Professionals just don’t rely on a few basic charts, rather they could create some custom charts to solve complex problems. Most of the custom or advanced visualization charts can be created by writing a few lines of python code.
In this course, you will be learning the following concepts and visualization charts using python libraries such as pandas, matplotlib, and seaborn-
- Installing python packages and defining path
- Creating a Line chart with matplotlib
- Putting labels and creating a dashed scatterplot
- Violin chart with seaborn
- More on the Violin chart
- Strip plot
- Boxplot
- Lmplot or align plot
Data visualization makes this task a little bit handier and fast. With the help of visual charts and graphs, we can easily find out the outliers, nulls, random values, distinct records, the format of dates, sensibility of spatial data, string and character encoding, and much more.
Moreover, you will be learning different charts to represent different kinds of data like categorical, numerical, spatial, textual, and much more.
- Bar Charts (Horizontal and Vertical)
- Line Charts
- Pie Charts
- Donut Charts
- Scatter Charts
- Grouped Bar Chart (Horizontal and Vertical)
- Segmented Bar Chart (Horizontal and Vertical)
- Time and series Chart
- Sunburst Chart
- Candlestick Chart
- OHLCÂ Charts
- Bubble Charts
- Dot Charts
- Multiple Line Charts and so on.
Most of the time data scientists pay little attention to graphs and focus only on numerical calculations which at times can be misleading. Data visualization is much crucial step to follow to achieve goals either in Data Analytics or Data Science to get meaningful insights or in machine learning to build an accurate model. The skills you learn in this course can be used in various domains related to data science and data analytics business intelligence and machine learning.
Who this course is for:
- Anyone curious to learn Data Visualization with Python, Power BI, and Plotly
- Machine learning enthusiasts
- Data Analyst
- Data Scientist
- Students and IT professionals
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