Modules is one of the best feature of Python. Except some core modules, you can install what you need and keep your Python setup smooth.
Changing a stored setting may mean reading its JSON file in Python. Python’s json module reads that file into Python values that a script can edit and save as JSON. I’ll explain how Python represents JSON data, then show how…
When a Python project needs a library, the first task is finding a package that fits what the code needs. pip installs Python packages from PyPI or another configured package index. This article shows how to search PyPI by purpose…
A value created in one Python run may still be useful after that run ends. Python’s pickle module turns an object into bytes that Python can reconstruct. I’ll show how to save and restore a Python value with pickle, then…
When a Python calculation needs the area under a function, an antiderivative may not be useful. scipy.integrate.quad estimates the definite integral of a one-variable function and returns the estimate with an error estimate. I’ll show how to pass a callable…
Splitting a set of numbers, such as test scores, into groups like quartiles lets you compare values by where they rank. pandas qcut does this by rank, putting a similar number of values in each group. This guide shows how…
When the next calculation needs an array of zeros that lines up with an array you already have, NumPy can build it for you. np.zeros_like creates that array, copying the shape and data type of the one you give it.…
When you’re about to fill a NumPy array with your own values straight away, you only need NumPy to set aside the space. np.empty creates that array without setting its values, and np.empty_like does the same using another array’s shape…
Data saved as a CSV (comma-separated values) file is plain text until you load it into something Python can work with. pandas read_csv() reads the file into a DataFrame, a table with labeled rows and columns. In this piece, I’ll…
Given a point’s x and y coordinates, you may need the angle it makes with the x-axis. np.arctan2 calculates that angle and uses the signs of both coordinates to put it in the right quadrant. You’ll get the angle in…
Fitting a line to data points means finding the slope and intercept that make the line’s errors as small as possible. SciPy’s minimize function searches for those values, starting from a guess you give it. The example writes the error…