Python libraries, what are they and which are the best?

Python is a programming language that stands out for its versatility and functionality. In addition to being open source, Python is interactive and cross-platform.

Among its main features, it has built-in fonts, as well as different types of libraries.

Thus, in this post, we talk about the Python libraries, what are they and which are the best?

Python libraries: definition

Broadly speaking, it should be noted that in programming a library is the set of functionalities that allow the user to carry out new tasks that could not be carried out before.

In other words, Python libraries are the set of implementations that allow this language to be coded, with the aim of creating an independent interface.

Each of the Python libraries has different modulesThe functions are specific and also vary depending on the operating system you are working with.

What is a basic Python library?

SimplyThe basic Python libraries or Python standard libraries (also called as such) are those that come bundled with Python. One of the most famous is Matplotlib.

Types of Python libraries, depending on their purpose

According to the objectives of Python libraries, there are different classifications. 

These are some types of Python libraries:

• Deep learning: They are focused on data prediction through Big Data.
• Machine learning: These libraries are useful for the machine learningThey improve information processing and problem solving in classification and regression data analysis.
• Numerical calculation: They prepare the data and provide important attributes for their calculation.
• Visualisation: They help to understand and comprehend the data in a more readable form. 
• Explainable Artificial Intelligence: They seek optimal results in Artificial IntelligenceThe project has been implemented through a variety of technological methodologies.
• Natural language processing: Based on the calculation of normalised frequencies, models are built with text data.

How to install a Python library?

Have you understood what Python libraries are? Now it is time to find out what your installation process is, using the "pip" module and the ".main()" method.

1. Get the scripts and pip files. 

Go into Python and look for the "Scripts" folder. Inside it, you will see different system modules. However, you will only be interested in "pip", open it!

2. Copy the address path

Once you open "pip", you will see a code, you must copy it. You will have to paste this code in the cmd of your computer's system.

Next, enter the command "pip install" with the name of the Python library or module you intend to install. 

3. Run the software

Finally, it will start installing your Python library. As you can see, the process is simple. If you follow these steps, you won't have any problems.

Top 9 Python libraries

As we warned before, there are all kinds of libraries in Python. We have carried out a selection of 9 Python libraries. And you, do you want to know which are the best Python libraries?

1. Matplotlib

Indeed, we have already mentioned Matplotlib. The fact is that this is the standard and best known Python library.

Matplotlib generates a wide variety of quality graphics for publishing online or on paper and without using many lines of code. 

Bar charts, histograms, time series, power spectra... are just some examples of the possibilities of this Python library.

2. TensorFlow

TensorFlow was developed by Google itself and is a key player in the numerical calculation. Its data flow diagrams are widely used in Deep Learning.

Its structure allows for the creation of a neural network, which serves to provide a new approach to the conceptualisation of mathematics.

3. PyTorch

In this case, Facebook was responsible for developing this Python library. It is also used in numerical computation and their graphics cards are critical for fast code execution.

4. Keras

Its task is to development of deep learning modelsThis allows neural network prototypes to be created quickly and efficiently. 

Also, this Python library is easy to use.

5. Scikit-learn

This example of Python libraries is designed to the construction of machine learning modelsand for data analysis.

Data regression, classification and clustering actions are possible. Its interface is simple, requiring only one line of code.

6. Pandas

Pandas is widely used in Data Science. The data are easy to work with, as their structures are made up of a series of data, as well as the Data Frame for two dimensions.

Statistics, economics, engineering, social sciences... this Python library is used in various sectors.

7. Seaborn

While data manipulation is the basis of Pandas, Seaborn focuses on the visualisation of statistical data to understand the data.

In this way, its interface is high-level as well as interactive.

8. Bokeh

Bokeh is also one of the Python libraries which stands out for its interactivity. Its graphics are very versatile and in real time, moreover.

9. NumPy

NumPy allows you to generate a universal data structureThis results in better data analysis, as there is an exchange of data between different algorithms.

Its vectors are multidimensional and the matrices have a large capacity.

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