I hope this helps. I’ve always had a hard time with matplotlib’s dates. Matplotlib requires a float format which is days since epoch. The helper functions num2date and date2num along with python builtin datetime can be used to convert to/from. The formatting business was lifted from this example. You can change an axis on any … Read more
The DataFrame plotting methods return a matplotlib AxesSubplot or list of AxesSubplots. (See the docs for plot, or boxplot, for instance.) You can then pass that same Axes to the next plotting method (using ax=ax) to draw on the same axes: ax = df_13_14_target[[‘month’,’2014_target_val’]].plot(x=’month’,linestyle=”-“, marker=”o”) df_13_14_target[[‘month’,’2013_val’,’2014_val’]].plot(x=’month’, kind=’bar’, ax=ax) import pandas as pd import matplotlib.pyplot as … Read more
As in the example you mentioned, call plt.scatter for each group: import numpy as np from matplotlib import pyplot as plt scatter_x = np.array([1,2,3,4,5]) scatter_y = np.array([5,4,3,2,1]) group = np.array([1,3,2,1,3]) cdict = {1: ‘red’, 2: ‘blue’, 3: ‘green’} fig, ax = plt.subplots() for g in np.unique(group): ix = np.where(group == g) ax.scatter(scatter_x[ix], scatter_y[ix], c = … Read more
It is probably easiest to just get the list of colors and cycle it yourself using itertools: import numpy as np from bokeh.plotting import figure, output_file, show # select a palette from bokeh.palettes import Dark2_5 as palette # itertools handles the cycling import itertools output_file(‘bokeh_cycle_colors.html’) p = figure(width=400, height=400) x = np.linspace(0, 10) # create … Read more
Thanks to this page in Google Groups I figured out how this can be done. Link here Edit 2015-10-20: looks like the google group link doesn’t work anymore unfortunately. It was a message from Sarah Bird @bokehplot. Edit 2017-01-18: Currently this would add multiple hover tool icons to the tool bar. This may cause problems. … Read more
Gnuplot can read column names from the first line, but you can still specify the column names normally as well. Therefore, this effectively skips the first line. Issue the command set key autotitle columnhead This tells gnuplot that the first line is not data, but is the column names to be used for the key. … Read more
You can do this with quiver, but it’s a little tricky to get the keyword arguments right. import numpy as np import matplotlib.pyplot as plt x = np.linspace(0, 2*np.pi, 10) y = np.sin(x) plt.figure() plt.quiver(x[:-1], y[:-1], x[1:]-x[:-1], y[1:]-y[:-1], scale_units=”xy”, angles=”xy”, scale=1) plt.show()
How to plot (high quality) emoji in matplotlib? [duplicate]
A one-line version of this excellent answer to plot the line of best fit is: plt.plot(np.unique(x), np.poly1d(np.polyfit(x, y, 1))(np.unique(x))) Using np.unique(x) instead of x handles the case where x isn’t sorted or has duplicate values.