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 is worth noting that it has built-in fonts, as well as different types of libraries.

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

Python libraries: definition

Broadly speaking, it should be noted that in programming a library responds to the set of functionalities that allow the custom software development company to carry out new tasks that could not be carried out before.

That is, Python libraries respond to 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 modules , with specific functions that also vary depending on the operating system you are working with.

What is a basic Python library?

Simply put , basic Python libraries or Python standard libraries (they are also called that) are those that come with Python.

Types of Python libraries, depending on your objectives

In accordance, with 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 machine learning , since they improve information processing and the resolution of classification problems and data regression analysis.
Numerical calculation: They prepare the data and offer important attributes for its calculation.
Visualization: They serve to understand and understand the data, in a more readable way.
Explainable Artificial Intelligence: They seek optimal results in Artificial Intelligence , carrying out various technological methodologies for software development services.
Natural language processing: Based on the calculation of normalized frequencies, models are built with text data.

How to install a library in Python?

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

1. Get the Scripts and pip files

Enter Python and look for the “Scripts” folder. Within 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. And you will have to paste this code into the cmd of your computer 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, your Python library will begin to install. As you can see, the process is simple. If you carry out these steps, you will not have any problems.

The 9 best Python libraries

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

1. Matplotlib

In fact, we have already referred to Matplotlib before. And this is the standard and best-known Python library.

With Matplotlib you can generate a wide variety of quality graphics to publish online or in paper without using many lines of code.

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

2. TensorFlow

For its part, TensorFlow was developed by Google itself and is key in numerical calculation . Its data flow diagrams are widely used in Deep Learning.

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

3. PyTorch

In this case, Facebook was in charge of developing this Python library. It is also used in numerical calculation and its graphics cards are essential for fast code execution .

4. Keras

Its mission is to develop deep learning models , so that neural network prototypes are created quickly and efficiently.

Likewise, this Python library is easy to use.

5. Scikit-learn

This example of Python libraries is designed for building machine learning models , as well as for data analysis.

Actions of regression, classification and grouping of the data are possible. Its interface is simple, since only one line of code is required.

6. Pandas

Pandas is widely used in Data Science. The data is easy to work with, since its 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 relies on the visualization 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 that stands out for its interactivity . Its graphics are very versatile and in real time, too.

9.NumPy

For its part, NumPy allows the generation of a universal data structure , which translates into better data analysis, since data is exchanged between different algorithms.

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

Python libraries, what are they and which are the best