The top 10 Python packages for developers to learn in 2022 are shown below.
Python has exploded in popularity in recent years, becoming a favorite among developers of all skill levels. More than 80% of programmers use it, making it one of the most well-liked programming languages. Many important tasks are streamlined by Python packages, including data analysis and visualization, machine learning model creation, online scraping for unstructured data, and effectively processing picture and text data. The top 10 Python packages for developers are listed below.
Python Data Analysis Library is known as Pandas. It contains a wide range of features that effectively manage massive amounts of data. It permits data import and is suitable for a variety of data types, including tabular, SQL, Excel, and JSON. One of the fantastic Python packages to learn in 2022 is this one.
More complicated coding involving dates and timings is made simpler with the Pendulum Python package. It manages time zones automatically and is more user-friendly. With a few minor exceptions, Pendulum will function just as effectively without any code modifications and will offer extra functionality not found in regular DateTime.
Python-dateutil offers several tools for manipulating dates and times. It is based on the straightforward and user-friendly DateTime module that comes with Python. The package is straightforward yet can significantly enhance your Python time series data handling experience.
The main Python tool for scientific computing is called NumPy. It combines the simplicity and adaptability of Python with the speed of C and Fortran-family programming languages. It makes sense why NumPy is used by such a large ecosystem of Python libraries and packages.
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.
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.
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 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.
It is the standard way of installing and managing packages in Python. it comes standard library with every Python distribution, allowing one to accomplish installs, uninstalls, updates, etc., from the command line.
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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