Python language is the popular and most commonly used by developers in creating mobile apps, games and other applications. A Python library is nothing but a collection of functions and methods which helps in solving complex data science related functions. Python also helps in saving amount of time while completing specific task.
Python has more than 130,000 libraries which are intended for different uses. Like python imaging library is used for image manipulation whereas Tensorflow is used for development of Deep Learning models using python.
There are multiple python libraries available for data science and some of them are already popular, remaining are improving day-by-day to reach their acceptance level by developers
Read: HOW TO SHAPE YOUR CAREER WITH DATA SCIENCE COURSE IN BANGALORE?
Here we are discussing some Python libraries which are used for Data Science:
1. Numpy
NumPy is the most popular library among developers working on data science. It is used for performing scientific computations like random number, linear algebra and Fourier transformation. It can also be used for binary operations and for treating images. If you are in the field of Machine Learning or Data science, you must have good knowledge of NumPy to process your real-time data sets. It is a perfect tool for basic and advanced array operations.
2. Pandas
PANDAS is open source library developed over Numpy and it contains Data Frame as its main data structure. It is used in high-performance data structures and analysis tools. With Data Frame, we can manage and store data from tables by performing manipulation over rows and columns. Panda library makes it easier for developer to work with relational data. Panda offers fast, expressive and flexible data structures.
Translating complex data operations using mere one or two commands is one of the most powerful feature of pandas and it also features time series functionality.
3. Matplotlib
This is a two dimensional plotting library of Python programming language which is very famous among data scientists. Matplotlib is capable of producing data visualizations such as plots, bar charts, scatterplots, and non-Cartesian coordinate’s graphs.
It is one of the important plotting libraries’ useful in data science projects. This is one of important library because of which Python can compete with scientific tools like MatLab or Mathematica.
4. SciPy
SciPy library is based on NumPy concept to solve complex mathematical problems. It comes with multiple modules for statistics, integration, linear algebra and optimization. This library also allows data scientist and engineers to deal with image processing, signal processing, Fourier transforms etc.
If you are going to start your career in data science field, SciPy will be very helpful to guide you for the whole numerical computations thing.
5. Scikit Learn
Scikit-Learn is open sourced and most rapidly developing Python libraries. It is used as a tool for data analysis and data mining. Mainly it is used by developers and data scientist for classification, regression and clustering, stock pricing, image recognition, model selection and pre-processing, drug response, customer segmentation and many more.
6. TensorFlow
It is a popular python framework used in deep learning and machine learning and it is developed by Google. It is an open source math library for mathematical computations. Tensorflow allows python developers to install computations to multiple CPU or GPU in desktop, or server without rewriting the code. Some popular Google products like Google Voice Search and Google Photos are built using Tensorflow library.
7. Keras
Keras is one of most expressive and flexible python library for research. It is considered as one of the coolest machine learning Python libraries which offers easiest mechanism for expressing neural networks and having all portable models. Keras is written in python and it has ability to run on top of Theano and TensorFlow.
Compared to other Python libraries, Keras is a bit slow, as it creates a computational graph using the backend structure and then perform operations.
8. Seaborn
It is data visualization library for python based on Matplotlib which is also integrated with pandas data structures. Seaborn offers high level interface for drawing statistical graphs. In simple words, Seaborn is extension of Matplotlib with advanced features.
Matplotlib is used for basic plotting such as bars, pies, lines, scatter plots and Seaborn is used for a variety of visualization patterns with few syntax and less complexity.
With the development of data science and machine learning, Python data science libraries are also advancing day by day. If you are interested in learning python libraries in depth, get NearLearn’s Best Python Training in Bangalore with real time projects and live case studies. Other than python, we provide training on Data science, Machine learning, Blockchain and React JS course. Contact us to get to know about our upcoming training batches and fees.
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