Python has many attractions, such as efficiency, speed and code readability, making data science enthusiasts programming language of choice. Python is usually the preferred data and machine learning experts, scientists hope to upgrade their application functionality.
Because of its wide use, Python has a large library that allows data scientists to more easily perform complex tasks without a lot of trouble to write code. The following is the scientific data before the three Python library.
1. NumPy
NumPy (Numerical Python abbreviation) is equipped with one useful resource for top-level library data can help scientists Python into a powerful scientific analysis and modeling tools. Popular open source database can be used under the BSD license. It is the basis for the Python library to perform tasks in scientific computing. NumPy is part of a larger ecosystem of tools based on open source Python, called SciPy.
His library for Python provides a number of data structures can effortlessly perform multi-dimensional arrays and matrix calculations. In addition to linear algebra and other mathematical equations outside, NumPy also be used as common data types multidimensional generic container.
In addition, it and other programming languages (such as C / C ++ and Fortran) perfectly integrated. NumPy library versatility it can be used quickly and easily in conjunction with various databases and tools.
2. Pandas
Pandas are another great libraries, scientific data can enhance your Python skills. And NumPy, as it belongs to the family SciPy open source software can be used under BSD license for free software.
Pandas provide versatile and powerful tool for organizing data structures and perform a large number of data analysis. This library for incomplete, unstructured and disorder actual data, and comes to shaping, polymerization, analysis tools and visualization of the data set.
This library has three types of data structures:
- Series: one-dimensional, uniform array
- DataFrame: a two-dimensional heterogeneous type column
- Panel: a three-dimensional, variable-sized array
3. Matplotlib
Matplotlib SciPy also part of the core package, and is available under the BSD license. It is a popular science Python library for generating simple yet powerful visualization. You can use Python framework for scientific data to generate creative graphics, charts, histograms, and other shapes and graphics without having to worry about writing lines of code.
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Conclusion:
Python programming language done well in terms of data processing and preparation, but not so important for complex scientific data analysis and modeling. Top Python framework for data science help to fill this gap, allowing you to perform complex mathematical calculations and create complex models to understand the data.