Data structures are the fundamental constructs that provides a particular way of organizing data so it can be accessed efficiently, depending on your use case.

• List
• Tuples

• Dictionaries
• Sets
• Boolean operators

• Functions
• MAP
• Working with files
• Time library
• JSON files

Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.

• Series
• Dataframes
• Basic commands
• Slices
• Transformations
• Map / apply functions
• Cleaning

Pandas groupby is used for grouping the data according to the categories and apply a function to the categories. An essential piece of analysis of large data is efficient summarization using aggregations.

• Pandas groupby
• Pandas aggregations
   

Data visualization is the most important step in the life cycle of data science, data analytics, or we can say in data engineering. It is more impressive, interesting and understanding when we represent our study or analysis with the help of colours and graphics. 

• Pandas visualizations: histograms, bar plots, scatter plots