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import pandas as pd import matplotlib.pyplot as plt from pathlib import Path p = Path('so_data/files') # specify the path to the files files = p.rglob('data_*.csv') # generator for all files based on rglob pattern for file in files: df = pd.read_csv(file, header=0, sep=',') # specify header row and separator as needed fig, (ax1, ax2) = plt ...
18 cze 2018 · What I'd like to do is to open every one of them and show them for 3 seconds. The data of the .txt is a [N x M] matrix. import numpy. import matplotlib.pyplot as plt. import time. while True: matrix = numpy.loadtxt('res/matrix_' + str(i) + '.txt') plt.clf() plt.imshow(matrix)
By far the most common way to create a figure is using the pyplot interface. As noted in Matplotlib Application Interfaces (APIs), the pyplot interface serves two purposes. One is to spin up the Backend and keep track of GUI windows. The other is a global state for Axes and Artists that allow a short-form API to plotting methods.
matplotlib.pyplot is a collection of functions that make matplotlib work like MATLAB. Each pyplot function makes some change to a figure: e.g., creates a figure, creates a plotting area in a figure, plots some lines in a plotting area, decorates the plot with labels, etc.
Each Axes also has a title (set via set_title ()), an x-label (set via set_xlabel ()), and a y-label set via set_ylabel ()). The Axes methods are the primary interface for configuring most parts of your plot (adding data, controlling axis scales and limits, adding labels etc.).
Matplotlib is a visualization library for Python. If you want to display something in a chart or graph, matplotlib can help you do that programmatically. In fact, many of the graphics you'll see in machine learning research papers or presentations are made with matplotlib.
18 sie 2023 · The .savefig() method in Matplotlib allows you to save the current figure to a file. You can specify the file format, the DPI, the face color, the edge color, and whether the figure is transparent. This gives you great control over your Matplotlib output.
