Introduction To Python Libraries

Hello, and welcome to my little corner of the internet! 

I'm Lalindi, and I'm super excited to have you here. On my blog, I document my life's journey from everyday adventures to meaningful experiences and everything in between. Today, I get to share with you one of the things I am most passionate about: coding with Python. I will be discussing some of the basic Python libraries that aided me in my journey to make coding smoother and much more pleasant in my first post. Whether a seasoned programmer or an absolute beginner, I hope you will find something useful, informative, and maybe even inspiring. So grab a cup of coffee, sit back, and let us see what wonders Python is made of. Thanks for stopping by and happy reading!

Introduction To Python Libraries


Typically a library is a place where a collection of books is displayed where readers can borrow them and read. There can be different categories of books as well as there can be copies of the same book as well. But in Python, library is something different from what we already know as a general library with books. 

A python library is a grouping of similar modules which includes code packages that are frequently utilized in various applications. This simplifies the Python programming for the programmer. These libraries enables developing programs with the same code instead of writing it repeatedly. Python libraries are essential in the domains of Data Science, Machine Learning, Data Visualization etc. 

Following are some most commonly used libraries: 

  • Numpy - Stands for 'Numerical Python' is one of the most commonly used libraries in Python. Numpy supports multi-dimensional data and large matrices.  It consists of in-built mathematical functions for easy computations. Many other python libraries are built on Numpy. 
  • SciPy - Stands for 'Scientific Python' is an open-source library used in high level scientific computations. This is built over an extension of Numpy. 
  • Pandas - Pandas are an important library in Python which is also open source. It provides tools for data manipulation such as merging, sorting, slicing, reshaping, aggregating etc. Pandas are mostly used by the data scientists. 
  • Matplotlib - This library is used in plotting numerical data in python. Using Matplotlib Line plots, Scatter plots, Bar charts, Histograms, Pie charts etc. can be plotted. This is popularly used in data analysis. 
  • Scikit-learn - This is an open source library working with complex data. This library operates in association with Numpy, SciPy and Matplotlib libraries. 
  • Seaborn - This is a Python data visualization library based on Matplotlib. It provides a high level interface for drawing attractive and informative statistical graphics. 
Now, let's discuss why Python libraries are useful: 

  1.  Code reusability – Once the code is written it can be used for similar future projects.
  2. Portability – Once the code is written it works across different systems and devices.
  3. Increased productivity - The initial code can be reused when it comes to a similar project without requiring the programmer to rewrite the same code, by improving productivity and saving time.
  4. Community support – Python has a large active community that contributes to library development and maintenance.
In conclusion, Python libraries are are a set of pre-written code that developers can utilize to streamline their work processes. They provide reusable functions, classes and modules that perform specific tasks by reducing the need to write the code from scratch. A wide range of functionalities including data manipulation, mathematical operations and web development can be covered using python libraries. 

Thanks for joining me in this tour of Python libraries. I really hope you found the information useful and inspiring. If you have any questions, thoughts, please do leave a comment below. Your feedback and engagement mean everything to me. Until next time, when I share more posts as I continue in this journey and discovery, stay tuned! Happy coding!

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