What is Python?
With the development of technology, Python has become a popular and versatile programming language. The very simple combination of signs and concepts of this language has made it easy to learn for all people, especially those who just want to step into the exciting world of programming.
One of the advantages of Python compared to other programming languages is the existence of many libraries and of course the open source and available, which leaves the hands of the programmer free to learn and use these libraries. Programmers can use different modules of this language for more speed and quality of work. Of course, these modules support the simple and advanced basics of life in the digital world; For example, you can use Python to write various functions in an Excel file.
7 suitable Python libraries for beginners
In this list, I will introduce 7 libraries that every programmer based on the Python language should know. However, if you do not intend to learn these libraries completely, it is better to have a general knowledge of how they work.
1. NumPy
The NumPy library is one of the most widely used Python libraries. Although this library has the capability of numerical calculations with very high speed and efficiency, its strength is in working with arrays. In Python, arrays consist of integers and combinations.
2. Pandas
The Pandas library is the backbone of data analysis in the Python programming language. The best library for those who want to learn how to work with numerical data and statistics is Pandas. With Pandas you can analyze, categorize, manipulate or calculate numbers.Suppose you have an excel file of grades of students in different grades. You can check the whole numbers in Excel using the pandas python library.
3. Matplotlib
One of the most important Python libraries for making graphs from numbers and data is matplotlib. In fact, creating different graphs quickly is one of the key skills of working with the Python programming language, but we suggest you do this with the matplotlib library.
4. OS
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OS is one of the Python libraries for working with operating systems. Maybe this library is not as attractive as others, but it is very useful. Especially when you want to communicate with the operating system from within the Python program and, for example, have your project files.
After receiving the files, you can perform various operations on them with commands such as os.rename() or os.replace(). Of course, the command os.chmod () is also needed to do things.
5. DATETIME
The DATETIME library is suitable for working with time and date. This library provides a method for measuring different times. Like measuring the days between two specific dates or counting leap years, etc. In the following code snippet, by entering the date of birth, we can find out how many days have passed since the birthday.
6. statsmodels
Statistical analysis is an important part of scientific projects. For this, you have several options to choose from among Python libraries: for example, NumPy or Pandas. The statsmodels library frees you to work with statistics and provides functions to estimate various statistical models and perform statistical tests.This library is built on top of NumPy and SciPy (another great library for scientific computing). Working with statsmodels, you can easily place a regression model on the data and have a summary of the results, which includes model parameters, r-squared metric, f-statistic, etc.
7. scikit-learn
If you are interested in learning machine learning or machine learning after learning Python, then the scikit-learn library should be at the top of your learning list. The scikit-learn library has a collection of experimental data and examples that you can use in Python programming. That is, if you are new and want to gain some experience in machine learning, ready data is available to you.Now you can analyze the data by calculating average values using the NumPy library or plotting with matplotlib. You can even manipulate the X and Y arrays with the DataFrame from the pandas library to get hands-on experience with data manipulation.I suggest you analyze the data in a cluster using the scikit-learn library. If you can carry out this process in a continuous and managed manner, you have practically taken a step towards mastering machine learning.
Conclusion
In this article, we have introduced a number of popular libraries suitable for beginners. Some of the libraries mentioned in this article have earned their place among the top Python programming language libraries. However, there are many other options that we could not include in the best list.Many libraries of this language are added to your program with its standard installation, and even if none of them are installed, it only takes a few clicks to install. After installation, it is very easy to add them to the project and incorporate them directly into the code correction or modification.
