In this tutorial, you’ll learn how to use the Response object from the Python requests library. When you make a request using the Python requests library, a Response object is returned. This is true, regardless if it’s a GET, POST, PUT, or another type of request. Knowing how to work with the Response object from […]
Python requests Response Object Explained Read More »
In this tutorial, you’ll learn how to use the Python requests library’s POST function to post data via HTTP. The Python requests library abstracts the complexities in making HTTP requests. The requests.post() function allows you to post data to a web resource. By the end of this tutorial, you’ll have learned: How the Python requests
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In this tutorial, you’ll learn how to use the Python requests library’s get method to fetch data via HTTP. The Python requests library abstracts the complexities in making HTTP requests. The requests.get() method allows you to fetch an HTTP response and analyze it in different ways. By the end of this tutorial, you’ll have learned:
Python requests: GET Request Explained Read More »
In this tutorial, you’ll learn how to use the Python frozenset data structure. The frozenset in Python is often overlooked and many Python users don’t even know that it exists. The frozenset is a data structure that emulates the set, but is immutable. By the end of this tutorial, you’ll have learned: What a Python
Python frozenset: Overview and Examples Read More »
In this tutorial, you’ll learn how to use the NumPy stack() function to join NumPy arrays along various axes. NumPy is an essential Python library for anyone working with data in Python. The NumPy stack() function allows you to combine NumPy arrays in different ways, along NumPy axes. By the end of this tutorial, you’ll
NumPy Stack: Join NumPy Arrays Along Different Axes Read More »
In this tutorial, you’ll learn how to use the NumPy squeeze() function. The np.squeeze() function allows you to remove single-dimensional entries from an array’s shape. This allows you to better transform arrays that aren’t shaped in the way that makes sense for the work that you’re doing. In short, the function returns the input array
NumPy Squeeze: Removing Dimensionality from NumPy Arrays Read More »
In this tutorial, you’ll learn how to use the Python divmod() function. The divmod() function takes two numbers are its arguments and returns their quotient and remainder. The function provides a number of incredibly helpful applications, such as being able to check divisibility and whether or not numbers are prime. By the end of this
Python Divmod Function & Examples Read More »
In this tutorial, you’ll learn how to use the NumPy repeat() function. The np.repeat() function is used to repeat arrays and provides significant opportunity to customize how the arrays are repeated. Being able to work with NumPy arrays is an important skill for data analysis, data science, and deep learning. By the end of this
NumPy Repeat Function: Repeating NumPy Arrays Read More »
In this tutorial, you’ll learn how to make 3D scatterplots using Matplotlib. Being able to visualize data in three dimensions can be an important step in clearly articulating data, especially in science and machine learning. By the end of this tutorial, you’ll have learned: How to plots 3D scatterplots using Matplotlib How to change size,
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In this tutorial, you’ll learn how to calculate percentiles in NumPy using the np.percentile() function. A percentile is a measure that indicates the value below which a percentage of observations in a group fall. For example, the 50th percentile will return the value from which half of the values are under. Knowing how to calculate
How to Calculate Percentiles in NumPy with np.percentile Read More »
In this tutorial, you’ll learn how to use the NumPy exponential function, np.exp(). The function raises the Euler’s constant, e, to a given power. Because Euler’s constant has many practical applications in science, math, and deep learning, being able to work with this function in meaningful ways is an asset for any Python user! By
NumPy Exponential: Using the NumPy.exp() Function Read More »
In this tutorial, you’ll learn how to change font sizes on a Matplotlib plot. You’ll learn everything you need to know to customize your Matplotlib plot to have exactly the font sizes you want. Data visualization is an incredible tool to better communicate your data. Being able to style your plot in the way you
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