Here’s what I’ve finally used: #!/usr/bin/env python3 import matplotlib from matplotlib import pyplot as plt from textwrap import wrap data = range(5) fig = plt.figure() ax = fig.add_subplot(111) ax.plot(data, data) title = ax.set_title(“\n”.join(wrap(“Some really really long long long title I really really need – and just can’t – just can’t – make it any – … Read more
I think you’re going to need separate lines for each segment: import numpy as np import matplotlib.pyplot as plt x, y = np.random.random(size=(2,10)) for i in range(0, len(x), 2): plt.plot(x[i:i+2], y[i:i+2], ‘ro-‘) plt.show() (The numpy import is just to set up some random 2×10 sample data)
Downgrade to matplotlib 3.2.2 until the bug in backtrader is fixed. Here is the fix pull request: https://github.com/mementum/backtrader/pull/418. pip uninstall matplotlib # or conda pip install matplotlib==3.2.2
Here’s a (very) slightly slicker version of Dan Allan’s answer: import matplotlib.pyplot as plt import pandas as pd import numpy as np import string df = pd.DataFrame({‘x’:np.random.rand(10), ‘y’:np.random.rand(10)}, index=list(string.ascii_lowercase[:10])) Which gives: x y a 0.541974 0.042185 b 0.036188 0.775425 c 0.950099 0.888305 d 0.739367 0.638368 e 0.739910 0.596037 f 0.974529 0.111819 g 0.640637 0.161805 h … Read more
The problem you are having is that bbox_inches=”tight” just removes all of the extra white space around your figure, it does not actually re-arrange anything in your figure, after it has been rendered. You might need to tweak the parameters you pass to tight_layout (tutorial) to get your desired effect. Hopefully this gets you pointed … Read more
You can use axhspan and/or axvspan like this: import matplotlib.pyplot as plt plt.figure() plt.xlim(0, 5) plt.ylim(0, 5) for i in range(0, 5): plt.axhspan(i, i+.2, facecolor=”0.2″, alpha=0.5) plt.axvspan(i, i+.5, facecolor=”b”, alpha=0.5) plt.show()
scatter([1,2,3], [2,4,5], s=1, facecolor=”0.5″, lw = 0) This sets the markersize to 1 (s=1), the facecolor to gray (facecolor=”0.5″), and the linewidth to 0 (lw=0).
Use the xticks command. import matplotlib.pyplot as plt t11 = [’00’, ’01’, ’02’, ’03’, ’04’, ’05’, ’10’, ’11’, ’12’, ’13’, ’14’, ’15’, ’20’, ’21’, ’22’, ’23’, ’24’, ’25’, ’30’, ’31’, ’32’, ’33’, ’34’, ’35’, ’40’, ’41’, ’42’, ’43’, ’44’, ’45’, ’50’, ’51’, ’52’, ’53’, ’54’, ’55’] t12 = [173, 135, 141, 148, 140, 149, 152, … Read more
To change the “%matplotlib inline” figure resolution on the notebook do: import matplotlib as mpl mpl.rcParams[‘figure.dpi’]= dpi I recommend setting the dpi somewhere between 150 and 300 if you are going to download/print the notebook. Ensure that %matplotlib inline runs before the mpl.rcParams[‘figure.dpi’]= dpi otherwise the magic command resets the dpi to its default value … Read more
Two retroactive ways: fig, ax = plt.subplots() # … fig.tight_layout() Or fig.subplots_adjust(bottom=0.2) # or whatever Here’s a subplots_adjust example: http://matplotlib.org/examples/pylab_examples/subplots_adjust.html (but I prefer tight_layout)