Anqi Wu

Anqi Wu is an aspiring Data Scientist and enthusiastic Python Freelancer. She is an incoming student for a Master's program in Analytics and builds her Python Freelancer profile on Upwork.Anqi is passionate about machine learning, statistics, data mining, programming, and many other data science related fields. She has proven her expertise during her undergraduate years, including multiple winning and top placements in mathematical modeling contests. She loves supporting and enabling data-driven decision-making, developing data services, and teaching.She is skilled at programming languages like Python, R, and SQL, actively delving into the world of Machine Learning and Deep Learning and traveling along her data science journey with joy. Data sensitivity and business acumen are her advantages to march towards the career path as a data scientist :)Here is a link to the author’s website: https://www.anqiwu.one/. She uploads data science blogs weekly to document her data science learning and practicing for the past week, along with some best learning resources and inspirational thoughts.I hope you enjoy this article! Cheers!

NumPy Meshgrid – A Simple Guide with Video

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In Python, the numpy.meshgrid() function turns coordinate vectors into coordinate matrices.  What’s the purpose of np.meshgrid()? The grid-like coordinate matrices separate the values for each dimension and are used widely in matrix manipulation, data visualization, and machine learning.  Here is the argument table of numpy.meshgrid(). If it sounds great to you, please continue reading, and … Read more

np.argsort() — A Simpe Illustrated Guide

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In Python, the numpy.argsort() function returns the indices that would sort an array in ascending order.  Here is the argument table of the numpy.argsort() function. If it sounds great to you, please continue reading, and you will fully understand the numpy.argsort() function through Python code snippets and vivid visualization. This tutorial is about numpy.argsort() function.  … Read more

np.gradient() — A Simple Illustrated Guide

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In Python, the numpy.gradient() function approximates the gradient of an N-dimensional array. It uses the second-order accurate central differences in the interior points and either first or second-order accurate one-sided differences at the boundaries for gradient approximation. The returned gradient hence has the same shape as the input array.  Here is the argument table of … Read more

np.zeros() — A Simple Illustrated Guide

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In Python, the numpy.zeros() function returns a new array of given shape and type, filled with zeros.  Here is the parameter table of numpy.zeros(). If it sounds great to you, please continue reading, and you will fully understand the numpy.zeros() function through Python code snippets and vivid visualization. Concretely, I will introduce its syntax and … Read more

np.where() – A Simple Illustrated Guide

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Python’s numpy.where(condition, x, y) function returns an array with elements from x where condition is True, and elements from y elsewhere.  When simply calling numpy.where(condition), it is the shorthand of np.asarray(condition).nonzero() and returns a tuple containing the indices of elements that meets the condition for each dimension. If it sounds great to you, please continue … Read more

pd.DataFrame.groupby() – A Simple Illustrated Guide

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In Python, the pandas.DataFrame.groupby() function splits a pandas.DataFrame into subgroups. It is a part of a full groupby operation, where we usually split the data, apply a function, and then combine the result. Here is the argument table of pandas.DataFrame.groupby(). If it sounds great to you, please continue reading, and you will fully understand the … Read more

np.argpartition() — A Simple Illustrated Guide

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In Python, the numpy.argpartition() function returns the indices that would partition an array along with a given axis based on the specified kth element(s). All elements smaller than the kth element will be moved before it and all larger elements behind it. The element order in the partitions is undefined. If provided with a sequence … Read more

np.diff() — A Simple Illustrated Guide

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In Python, the numpy.diff() function calculates the n-th discrete difference between adjacent values in an array along with a given axis. For higher-order differences calculation, numpy.diff() runs recursively to the output of the previous execution. Here is the argument table of numpy.diff(): If it sounds great to you, please continue reading, and you will fully … Read more

Python os.walk() – A Simple Illustrated Guide

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According to the Python version 3.10.3 official doc, the os module provides built-in miscellaneous operating system interfaces. We can achieve many operating system dependent functionalities through it. One of the functionalities is to generate the file names in a directory tree through os.walk(). If it sounds great to you, please continue reading, and you will … Read more