Data Visualization with Python and Plotly

Data Visualization is one of the indispensable topics in data science and machine learning. It is the process of creating interactive visuals to understand trends and variations and derive meaningful insights from the data. We all know that data is the new oil. Likewise, if oil is not processed, it is of no use, and to derive relevant insights from data for making critical business decisions, it should be cleaned and processed. 

Data visualization makes this task a little bit more handy 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, the sensibility of spatial data, string and character encoding, and much more. 

In this learning course, 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

• 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 the numerical calculations, which at times can be misleading. Data visualization is a 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.