Matplotlib

bootstrap_plot() – Pandas Plotting Module

A bootstrap plot is a graphical representation of uncertainty in a characteristic chosen from within a population. While we can usually calculate data confidence levels mathematically, gaining access to the desired characteristics from some populations is impossible or impracticable. In this case, bootstrap sampling and the bootstrap plot come to our aid. This article will …

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How to Install Matplotlib on PyCharm?

Matplotlib is the most important Python library for data visualization and plotting. Every data scientist, machine learning engineer, and financial analyst working with Python needs it! Problem Formulation: Given a PyCharm project. How to install the Matplotlib library in your project within a virtual environment or globally? Here’s a solution that always works: Open File …

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Plotting a Load-Duration Curve with Python

You can check out the code in this article in the interactive Jupyter notebook here (Google Colab). Introduction A popular query in Google is about load-duration curves. Some of the questions are: What is a load-duration curve? What is the importance of a load-duration curve? How do you calculate a load-duration curve? What is the …

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The Pandas Plotting Module: Generating Andrews Curves

Andrews curves are used to identify structure in a multi-dimensional data set. By reducing complex data to a two-dimensional graph, we can more easily identify variables in the data that are associated, form clusters, or are outliers. We’ll show you how to plot such graphs, but before we get to that, let’s ensure every reader …

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How to Change the Figure Size for a Seaborn Plot?

Seaborn is a comprehensive data visualization library used for the plotting of statistical graphs in Python. It provides fine-looking default styles and color schemes for making more attractive statistical plots. Seaborn is built on the top portion of the matplotlib library and is also integrated closely with data structures from pandas.                                                             How to change …

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Smoothing Your Data with the Savitzky-Golay Filter and Python

This article deals with signal processing. More precisely, it shows how to smooth a data set that presents some fluctuations, in order to obtain a resulting signal that is more understandable and easier to be analyzed. In order to smooth a data set, we need to use a filter, i.e. a mathematical procedure that allows …

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How To Plot SKLearn Confusion Matrix With Labels?

Summary: The best way to plot a Confusion Matrix with labels, is to use the ConfusionMatrixDisplay object from the sklearn.metrics module. Another simple and elegant way is to use the seaborn.heatmap() function. Note: All the solutions provided below have been verified using Python 3.9.0b5. Problem Formulation Imagine the following lists of Actual and Predicted values …

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