In recent years, Python has spread like wildfire, and many developers, from beginners to experts have taken a liking to it. It is one of the most popular programming languages which is used by more than 80% of the developers. Python packages streamline many significant processes, like analyzing and visualizing data, building ML models, capturing unstructured data from the web, and processing image and text information efficiently. Here are the top 10 Python packages that every developer should learn.
Pandas: Pandas stand for Python Data Analysis Library. It has an extensive set of features that handle large data efficiently. It is well suited for different kinds of data be it Tabular, SQL or Excel, or JSON, and allows importing data. This is one of the amazing Python packages to learn in 2022.
Pendulum: The Pendulum Python package makes it easier to do more complex coding involving dates and times. It's more intuitive to work with, and it manages time zones automatically. With only a few exceptions, Pendulum will work just as well, without the need to modify the code, while providing extra features not present in plain-old DateTime.
Python-dateutil: Python-dateutil provides several dates and time manipulation capabilities. It builds on the DateTime module that is built into Python and is simple and easy to use. The package is simple, but can dramatically improve your Python experience when handling time series data.
NumPy: NumPy is the primary tool for scientific computing in Python. It combines the flexibility and simplicity of Python with the speed of languages like C and Fortran. No wonder there is a huge ecosystem of Python packages and libraries drawing on the power of NumPy.
Pywin32: Pywin32 is a must-have package, particularly for Windows Python programming. It provides access to many of the native Windows API functions, allowing you to do things. It enables you to access the Win32 application programming interface (API) on Python.
Pytest: The Pytest package provides a variety of modules to help you do this. Whether it's a simple unit test or a more complex functional test, Pytest can help you write it.
Seaborn: The Seaborn package can easily create complex heatmaps, violin plots, joint plots, multi-plot grids, and many other types of plots. It provides beautiful default styles and color palettes to make statistical plots more attractive. It is built on top of the matplotlib library and is closely integrated into the data structures from pandas.
MoviePy: MoviePy is to videos what Pillow is to images. It provides a range of functionalities for common tasks associated with importing, modifying, and exporting video files. Like Pillow, MoviePy is not intended as a tool for advanced data manipulation. For most standard tasks involving videos in Python code, MoviePy gets the job done quite well.
Pip: Pip is the standard way of installing and managing packages in Python. Pip comes standard library with every Python distribution, allowing one to accomplish installs, uninstalls, updates, etc., from the command line.
Matplotlib: Matplotlib is the foundation of every other visualization library. This can be used to create basic graphs like line plots, histograms, scatter plots, bar charts, and pie charts. It allows you to freely choose how to display labels, grids, legends, etc.
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