Cheatsheets Alternatives
Similar projects and alternatives to cheatsheets
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Pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
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SonarLint
Clean code begins in your IDE with SonarLint. Up your coding game and discover issues early. SonarLint is a free plugin that helps you find & fix bugs and security issues from the moment you start writing code. Install from your favorite IDE marketplace today.
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manim
A community-maintained Python framework for creating mathematical animations. (by ManimCommunity)
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Fast-F1
FastF1 is a python package for accessing and analyzing Formula 1 results, schedules, timing data and telemetry
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Scout APM
Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.
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d3
Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:
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Pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
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awesome-python
A curated list of awesome Python frameworks, libraries, software and resources
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Scrapy
Scrapy, a fast high-level web crawling & scraping framework for Python.
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cheatsheets reviews and mentions
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Visualizing Supabase Data using Metabase
Data helps organizations make better decisions. With a programming language like Python to analyze your data and transform data into visual representations, you can effortlessly tell the story of your business. One way to create customized visuals from your data would be to use data visualization libraries in Python like Matplotlib, Seaborn, Ggplot2, Plotly, or Pandas. When you want to accomplish this task with little or no code (not even SQL), you might consider using tools like Metabase.
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Plotting Bookmarks with Flask, Matplotlib, and OAuth 2.0
To plot the labels and values you will use Matplotlib. Once you have your graph you can save it and render in a view.
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NLTK Lexical Dispersion Plot - word offset to percentile in the x-axis
# Natural Language Toolkit: Dispersion Plots # # Copyright (C) 2001-2022 NLTK Project # Author: Steven Bird # URL: # For license information, see LICENSE.TXT import numpy as np """ A utility for displaying lexical dispersion. """ def dispersion_plot(text, words, ignore_case=False, title="Lexical Dispersion Plot"): """ Generate a lexical dispersion plot. :param text: The source text :type text: list(str) or enum(str) :param words: The target words :type words: list of str :param ignore_case: flag to set if case should be ignored when searching text :type ignore_case: bool """ try: from matplotlib import pylab except ImportError as e: raise ValueError( "The plot function requires matplotlib to be installed." "See https://matplotlib.org/" ) from e text = list(text) words.reverse() if ignore_case: words_to_comp = list(map(str.lower, words)) text_to_comp = list(map(str.lower, text)) else: words_to_comp = words text_to_comp = text points = [ (x, y) for x in range(len(text_to_comp)) for y in range(len(words_to_comp)) if text_to_comp[x] == words_to_comp[y] ] if points: x, y = list(zip(*points)) else: x = y = () pylab.plot(x, y, "b|", scalex=0.1) pylab.yticks(list(range(len(words))), words, color="b") pylab.title(title) pylab.xlabel("Word Offset") pylab.show() if __name__ == "__main__": from nltk.corpus import gutenberg words = ["Elinor", "Marianne", "Edward", "Willoughby"] dispersion_plot(gutenberg.words("austen-sense.txt"), words
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Python in Action: Machine Learning
4. Matplotlib is the most popular Python library for data visualization and 2-D plotting.
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[OC] Monaco Grand Prix 2022 - Verstappen fastest lap
Dataset acquired using FastF1 API https://theoehrly.github.io/Fast-F1/ Generated using NumPy https://numpy.org/ and MatPlotLib (python) https://matplotlib.org/
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Python cheatsheet and snippets for beginners
import math #math https://docs.python.org/3/library/math.html #matplotlib https://matplotlib.org/ #numpy https://numpy.org/ #math -> Some more complicated calculations print(math.sqrt(15)) print(math.sin(math.pi/6)) print(math.cos(math.radians(60)))) #numpy more advanced math and amazing helper functions #matplotlib plotting charts import matplotlib.pyplot as plt import numpy as np plt.style.use('_mpl-gallery') # make date x = np.linspace(0, 10, 100) y = 4 + np.sin(x) # plot fig, ax = plt.subplots() ax.plot(x, y, linewidth=2.0) ax.set(xlim=(0, 8), xticks=np.arange(1, 8), ylim=(0, 8), yticks=np.arange(1, 8)) # plt.show() plt.savefig("matplotlib.png")
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ordering and making a chart
Matplotlib
- Resumão de Python para iniciantes com aulas! [PT-BR]
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Does pip install native dependencies?
apt show python3-matplotlib Package: python3-matplotlib Version: 3.1.2-1ubuntu4 Priority: optional Section: universe/python Source: matplotlib Origin: Ubuntu Maintainer: Ubuntu Developers <[[email protected]](mailto:[email protected])> Original-Maintainer: Sandro Tosi <[[email protected]](mailto:[email protected])> Bugs: https://bugs.launchpad.net/ubuntu/+filebug Installed-Size: 13,7 MB Depends: python3-dateutil, python-matplotlib-data (>= 3.1.2-1ubuntu4), python3-pyparsing (>= 1.5.6), python3-six (>= 1.4), libjs-jquery, libjs-jquery-ui, python3-numpy (>= 1:1.16.0~rc1), python3-numpy-abi9, python3 (<< 3.9), python3 (>= 3.8~), python3-cycler (>= 0.10.0), python3-kiwisolver, python3:any, libc6 (>= 2.29), libfreetype6 (>= 2.2.1), libgcc-s1 (>= 3.0), libpng16-16 (>= 1.6.2-1), libstdc++6 (>= 5.2) Recommends: python3-pil, python3-tk Suggests: dvipng, ffmpeg, gir1.2-gtk-3.0, ghostscript, inkscape, ipython3, librsvg2-common, python-matplotlib-doc, python3-cairocffi, python3-gi, python3-gi-cairo, python3-gobject, python3-nose, python3-pyqt5, python3-scipy, python3-sip, python3-tornado, texlive-extra-utils, texlive-latex-extra, ttf-staypuft Enhances: ipython3 Homepage: http://matplotlib.org/ Task: ubuntustudio-video Download-Size: 4.459 kB APT-Manual-Installed: no APT-Sources: http://de.archive.ubuntu.com/ubuntu focal/universe amd64 Packages Description: Python based plotting system in a style similar to Matlab (Python 3) Matplotlib is a pure Python plotting library designed to bring publication quality plotting to Python with a syntax familiar to Matlab users. All of the plotting commands in the pylab interface can be accessed either via a functional interface familiar to Matlab users or an object oriented interface familiar to Python users. . This package contains the Python 3 version of matplotlib.
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News algorithm project-Help needed
This sounds very vague to me, but Python can probably do what you are imagining. For example, for graphs of statistical relationships between data, there is https://matplotlib.org/ and https://seaborn.pydata.org/. If you want to go deeper into machine learning, there is https://scikit-learn.org/stable/index.html and https://www.tensorflow.org/ for example. Also, take a look at https://pandas.pydata.org for tabular data of different kinds.
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Plotting graphs
You better use Python with matplotlib, which is very similar to Matlab.
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Good software for creating simple graphics for thesis and presentation
To plot some sensor data I use Plotly or Matplotlib
- 20 Artikel Terpopuler di Wikipedia Indonesia selama Januari - Maret 2022. Highlight isu: Kejuaraan AFF, Layangan Putus, Kukira Kau Rumah, Dorce Gamalama, perang Rusia-Ukraina, Jusuf Hamka. (Sumber: Wikimedia REST API, 8/4/2022)
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Coding for Astronomers?
With these, you can make data that you then feed into Python (Matplotlib) to make some nice plots.
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Bahrain Race - Relative lap times (Driver and Team box plots)
This was also my first attempt at using the impressive Fast-F1 data and Python Matplotlib.
Stats
matplotlib/cheatsheets is an open source project licensed under BSD 2-clause "Simplified" License which is an OSI approved license.
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