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python_practice

Hello, I have started coding in python and i have challenged myself to code for a year. I will be updating my progress here on Github, you can click on view github above.

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I have practiced coding in hackerrank for python https://www.hackerrank.com/chandanaudupaof1 and i have learnt and practiced python for data science in datacamp https://www.datacamp.com/profile/chandanaudupaofficial

Learnings:

PYTHON LIBRARY - Numpy

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Numpy is used to build n-dimensional array that will be useful to manipulate the data from the dataset to achieve desired outputs/results. It is also used to find mean, median and standard deviation and many more of the given data. Some of the popular numpy function are: numpy.array(), numpy.mean(), numpy.std(),numpy.median() etc.

PYTHON LIBRARY - Matplotlib

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Matplotlib is a very powerful library that is used for plotting and data visualization. With this library, we can plot histograms, scatter and line plots. Some of the popular matplotlib functions are: matplotlib.pyplot.plot(), matplotlib.pyplot.scatter(), matplotlib.pyplot.hist(), matplotlib.pyplot.show(), matplotlib.pyplot.xticks(), matplotlib.pyplot.yticks(), matplotlib.pyplot.text() etc.

PYTHON LIBRARY - Scipy

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SciPy is an Open Source Python-based library, which is used in mathematics, scientific computing, Engineering, and technical computing.SciPy contains varieties of sub packages which help to solve the most common issue related to Scientific Computation. SciPy is the most used Scientific library only second to GNU Scientific Library for C/C++ or Matlab's.

Some of the sub packages of scipy are: File input/output - scipy.io, Special Function - scipy.special, Linear Algebra Operation - scipy.linalg, Interpolation - scipy.interpolate, Optimization and fit - scipy.optimize, Statistics and random numbers - scipy.stats, Numerical Integration - scipy.integrate, Fast Fourier transforms - scipy.fftpack, Signal Processing - scipy.signal, Image manipulation – scipy.ndimage. It is built over numpy.

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Trying to learn python and code everyday

https://chandanagiridhar.github.io/python_practice/

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