Data analysis and visualization
Python programming is popular because of its easy usage and the availability of libraries for scientific computing, text computation, data analysis, machine learning, and much more. Data analysis is a systematic process. Unknown facts, hidden patterns, summary data, and a lot of other information can be obtained using data analysis. Data analysis is also treated as a subset of data science, and it has been booming with the use of Python and its features.
In this section, we will be analyzing some datasets, exploring some of the important features of pandas, and visualizing the results using plotly.
Analyzing data generally involves a few basic steps:
- Identify: Identify the source of data or the origin of data, such as a website, PDF file, or image.
- Collect: Collect the identified data using scraping or other techniques. Storing data is also important here.
- Clean: Preprocess and clean the collected data. Clean data is easier to process...
