Iterative processes
Repetitive tasks can be automated using computers. This is because computers do well in performing identical tasks without making errors. Iteration is the process of executing a set of statements repeatedly. This process is widely used in Python. There is a myriad of features provided by the programming language to make the iterative process easy. The most common type of iteration used in Python is the "for the statement". However, there is also the "while statement" that offers another way of performing iteration but is useful in slightly different circumstances.
Recursion
The recursion function is accepted in Python. This means that a function that has been defined can call itself. Programmers can loop through data to reach a result. When using recursion, one may end up writing a function that never terminates or uses a large amount of memory. This can, however, be avoided when the recursion function is written correctly. If you are new to programming in Python, you may struggle to grasp how exactly this works. The best way to learn recursion is to test and modify. Once you learn how it works, you will find that it is a quite efficient and mathematically elegant approach to Python programming.
Data Visualization
A graphic representation of data to obtain useful trends and patterns is the definition of data visualization. Python is equipped with multiple comprehensive libraries that support the creation of superior quality informative and interactive statistical graphics, both 2D and 3D. Some of the data visualization libraries in Python are:
- Matplotlib
Supports the creation of scatter plots, pie charts, bar graphs, line charts, and histograms. It is one of the most popular visualization libraries.
- Seaborn
This library is built on top of Matplotlib. It boasts of a high-level interface and interactive designs.
- Pandas
This is another awesome library that supports time-series analysis and data manipulation. It is also built on top of Matplotlib.
- Plotly
Supports the creation of interactive multi-dimensional plots. It makes the data analysis process simple.