Redash VS matplotlib

Compare Redash vs matplotlib and see what are their differences.

Redash

Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data. (by getredash)

matplotlib

matplotlib: plotting with Python (by matplotlib)
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Redash matplotlib
9 11
19,987 14,603
2.1% 2.2%
7.9 10.0
4 days ago 3 days ago
Python Python
BSD 2-clause "Simplified" License Python License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Redash

Posts with mentions or reviews of Redash. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-10-24.

matplotlib

Posts with mentions or reviews of matplotlib. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-10-30.
  • Problem with surface plot color and legend
    1 project | reddit.com/r/learnpython | 24 Nov 2021
    # https://old.reddit.com/r/learnpython/comments/r1etmt/problem_with_surface_plot_color_and_legend/ # AmericaRL_03.py # Comparação entre random walk e difusão em 1d import numpy as np import matplotlib.pyplot as plt M = 100000 # Número de walkers L = 100 # Tamanho da malha # A cada intervalo de tempo, mover o walker e propagar a difusão p = 0.1 # Probabilidade de andar pinv = 1.0 - p nsteps = 2001 # Número de intervalos de tempo # Iniciando as concentrações c = np.zeros((2, 2 * L + 1, 2 * L + 1)) i0 = 0 i1 = 1 c[:, L, L] = M # c[:,L,L] corresponde a (x,y) = (0,0) edgesdiff = np.array(range(-L - 1, L + 1)) - 0.5 xc = 0.5 * (edgesdiff[:-1] + edgesdiff[1:]) xx, yy = np.meshgrid(xc, xc) D = p noutput = 100 for it in range(nsteps): # Executar a etapa na equação de difusão for ix in range(1, len(c[0]) - 1): for iy in range(1, len(c[0]) - 1): # Usar i0 e gerar i1 c[i1, ix, iy] = c[i0, ix, iy] + D * ( c[i0, ix - 1, iy] + c[i0, ix + 1, iy] - 4 * c[i0, ix, iy] + c[i0, ix, iy - 1] + c[i0, ix, iy + 1] ) # Inverter i0 e i1 ii = i1 i1 = i0 i0 = ii # Plotar as concentrações if np.mod(it, noutput) == 0: fig = plt.figure() ax = fig.add_subplot(111, projection="3d") # ax.cla() diff = ax.plot_surface(xx, yy, c[0, :, :], cmap="Reds", label="Difusão") plt.title("Tempo = {}, M = {}, p = {}".format(it, M, p)) ax.set_xlabel("Distância percorrida (x)") ax.set_ylabel("Distância percorrida (y)") ax.set_zlabel("Concentração") # ax.legend() fails getting proper label key color in 3D plots # # AttributeError missing _facecolors2d and _edgecolors2d are raised # in 3D projection method get_facecolor() used by legend handler # # Is open issue since 2015 # https://github.com/matplotlib/matplotlib/issues/4067 if False: # OP's way: Set values manually to keep legend() quiet diff._facecolors2d = diff._facecolor3d diff._edgecolors2d = diff._edgecolor3d ax.legend() # But then problems with legend() getting proper legend key color # default (blue) is used instead of a value from set cmap (Reds) else: # DIFFERENT FIX: Draw legend key and legend label manually # # First get suitable cmap color (instead blue default) # https://stackoverflow.com/a/25408562 from matplotlib.cm import get_cmap cmap = get_cmap('Reds') my_red_rgba = cmap(0.5) # e.g. a color in middle of range (0..1) # Then insert own artist for legend key and legend label # https://matplotlib.org/stable/tutorials/intermediate/legend_guide.html import matplotlib.patches as mpatches red_patch = mpatches.Patch(color=my_red_rgba, label='Difusão') ax.legend(handles=[red_patch]) # plt.show() plt.savefig('tempo_{}.png'.format(it),dpi = 600) plt.pause(0.001) ax.cla() # is nicer placed here instead above
  • Python 3.8, 3.9 or 3.10 for new projects?
    3 projects | reddit.com/r/Python | 30 Oct 2021
    matplotlib supports 3.10 since May
  • Top 10 Python Libraries for Machine Learning
    14 projects | dev.to | 9 Sep 2021
    Website: https://matplotlib.org/ Github Repository: https://github.com/matplotlib/matplotlib Developed By: Micheal Droettboom, Community Primary purpose: Data Visualization
  • Should you learn Julia or Python for Machine Learning?
    8 projects | reddit.com/r/learnmachinelearning | 15 Aug 2021
    But, now we have to get used to Python's library of Machine Learning packages: tensorflow, numpy, matplotlib, and finally pandas
  • Is there a way to improve this code?
    1 project | reddit.com/r/learnpython | 3 Apr 2021
  • Top 10 Python Libraries
    14 projects | dev.to | 24 Mar 2021
    Download the latest version of Matplotlib or visit its GitHub repo for more information.
  • Matplotlib: why do plot and axes interfaces use different method names to do the exact same thing?
    1 project | reddit.com/r/learnpython | 5 Mar 2021
    I think sloppiness explains it, this explains how you can fix it ;)
  • How I create GitHub project reporting from scratch
    10 projects | dev.to | 5 Mar 2021
    Firstly, I tried the most popular visualization library matplotlib. But its configuration didn’t seem clear to me, so moved on with other options.
  • Valentine's Day Challenge
    1 project | reddit.com/r/cryptography | 17 Feb 2021
    That would explain the link to https://matplotlib.org/ in the file...
  • What API suits the creation of a modern dynamic GUI used primarily for plotting in real time?
    2 projects | reddit.com/r/learnpython | 14 Feb 2021
    Matplotlib? https://matplotlib.org/

What are some alternatives?

When comparing Redash and matplotlib you can also consider the following projects:

plotly - The interactive graphing library for Python (includes Plotly Express) :sparkles:

PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications

pygal - PYthon svg GrAph plotting Library

bokeh - Interactive Data Visualization in the browser, from Python

bqplot - Plotting library for IPython/Jupyter notebooks

Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]

plotnine - A grammar of graphics for Python

VisPy - Main repository for Vispy

ggplot - ggplot port for python

seaborn - Statistical data visualization in Python