The z-label does not show up in my figure. What is wrong?
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.set_xlabel("x")
ax.set_ylabel("y")
ax.set_zlabel("z")
plt.show()
Output
Neither ax.set_zlabel("z") nor ax.set(zlabel="z") works. The x- and y-labels work fine.
That's a padding issue.
labelpadfloat The distance between the axis label and the tick labels.
Defaults to rcParams["axes.labelpad"] (default: 4.0) = 4.
You can use matplotlib.axis.ZAxis.labelpad to adjust this value for the z-axis :
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111, projection="3d")
ax.set_xlabel("x")
ax.set_ylabel("y")
ax.set_zlabel("StackOverflow", rotation=90)
ax.zaxis.labelpad=-0.7 # <- change the value here
plt.show();
Output :
Related
I'm trying to control the zorder of different plots across twinx axes. How can I get the blue noisy plots to appear in the background and the orange smoothed plots to appear in the foreground in this plot?
from matplotlib import pyplot as plt
import numpy as np
from scipy.signal import savgol_filter
random = np.random.RandomState(0)
x1 = np.linspace(-10,10,500)**3 + random.normal(0, 100, size=500)
x2 = np.linspace(-10,10,500)**2 + random.normal(0, 100, size=500)
fig,ax1 = plt.subplots()
ax1.plot(x1, zorder=0)
ax1.plot(savgol_filter(x1,99,2), zorder=1)
ax2 = ax1.twinx()
ax2.plot(x2, zorder=0)
ax2.plot(savgol_filter(x2,99,2), zorder=1)
plt.show()
Similar to this thread, though not ideal, this is an approach using twiny along with twinx.
# set up plots
fig, ax1 = plt.subplots()
ax2 = ax1.twinx()
ax3 = ax1.twiny()
ax4 = ax2.twiny()
# background
ax1.plot(x1)
ax2.plot(x2)
# smoothed
ax3.plot(savgol_filter(x1,99,2), c='orange')
ax4.plot(savgol_filter(x2,99,2), c='orange')
# turn off extra ticks and labels
ax3.tick_params(axis='x', which='both', bottom=False, top=False)
ax4.tick_params(axis='x', which='both', bottom=False, top=False)
ax3.set_xticklabels([])
ax4.set_xticklabels([])
# fix zorder
ax1.set_zorder(1)
ax2.set_zorder(2)
ax3.set_zorder(3)
ax4.set_zorder(4)
plt.show()
Output:
When using ax.grid() and moving the spines to the middle of the plot, the grid lines go over the axes labels. Any way to stop this and move the axes labels to "front"?
EDIT: It is the ticks labels (the numbers) I'm interested in fixing, not the axis label, which can be easily moved.
EDIT: made the MWE and image match exactly
EDIT: matplotlib version 2.0.0
#!/usr/bin/env python
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure()
ax = plt.gca()
ax.minorticks_on()
ax.grid(b=True, which='major', color='k', linestyle='-',alpha=1,linewidth=1)
ax.grid(b=True, which='minor', color='k', linestyle='-',alpha=1,linewidth=1)
x = np.linspace(-5,5,100)
y = np.linspace(-5,5,100)
plt.plot(x,y)
plt.yticks([-5,-4,-3,-2,-1,0,1,2,3,4,5])
ax.spines['left'].set_position(('data', 0))
plt.show()
I am beginner with python (3.4) and matplotlib. I want to create a wedge with the following code:
import matplotlib.pyplot as plt
import matplotlib.patches as patches
fig1 = plt.figure()
ax1 = fig1.add_subplot(111, aspect='equal')
ax1.add_patch(patches.Wedge(center=(0,0), r=0.9, theta1=90, theta2=120, facecolor="red", label="Test"))
plt.xlim(-1, 1)
plt.ylim(-1, 1)
fig1.savefig('wedge1.png', dpi=90, bbox_inches='tight')
plt.show()
All Looks fine, but the Label isn't in the plot? Any idea?
You are missing a plt.legend(). You just need to add it anywhere before the plt.show (also before fig1.savefig if you want it saved in the image) and after all your plots:
import matplotlib.pyplot as plt
import matplotlib.patches as patches
fig1 = plt.figure()
ax1 = fig1.add_subplot(111, aspect='equal')
ax1.add_patch(patches.Wedge(center=(0,0), r=0.9, theta1=90, theta2=120, facecolor="red", label="Test"))
plt.xlim(-1, 1)
plt.ylim(-1, 1)
plt.legend() # <--- here
fig1.savefig('wedge1.png', dpi=90, bbox_inches='tight')
plt.show()
Have a look here for further details on how to use legends.
I am doing a simple scatterplot using Pythons scatterplot. But no matter how I set my axis, and no matter that I don't have any negative values I get negative values at the x-axis. How do I force the axis to start at 0?
My code:
fig, ax = plt.subplots(1)
ax.scatter(lengths,breadths, alpha=0.3, color="#e74c3c", edgecolors='none')
spines_to_remove = ['top', 'right']
for spine in spines_to_remove:
ax.spines[spine].set_visible(False)
ax.xaxis.set_ticks_position('none')
ax.yaxis.set_ticks_position('none')
ax.xaxis.set_view_interval(0,400)
ax.yaxis.set_view_interval(0,90)
figname = 'scatterlengthsbreadths.pdf'
fig.savefig(figname, bbox_inches='tight')
You can use ax.set_xlim(lower_limit, upper_limit) to choose your x-limits. Note that there is a similar command ax.set_ylim for the y-limits.
Note that if you're just using the pyplot interface, i.e. without using fig and ax, then the command is plt.xlim().
For example:
import matplotlib.pyplot as plt
x = [1,2,3]
y = [4,5,6]
fig, ax = plt.subplots()
ax.plot(x, y)
ax.set_xlim(0, 10)
plt.show()
I am working on matplotlib and created some graphs like bar chart, bubble chart and others.
Can some one please explain with an example what is difference between line graph and sparkline graph and how to draw spark line graphs in python using matplotlib ?
for example with the following code
import matplotlib.pyplot as plt
import numpy as np
x=[1,2,3,4,5]
y=[5,7,2,6,2]
plt.plot(x, y)
plt.show()
the line graph generated is the following:
But I couldn't get what is the difference between a line chart and a spark lien chart for the same data. Please help me understand
A sparkline is the same as a line plot but without axes or coordinates. They can be used to show the "shape" of the data in a compact way.
You can cram several line plots in the same figure just by using subplots and changing properties of the resulting Axes for each subplot:
data = np.cumsum(np.random.rand(1000)-0.5)
data = data - np.mean(data)
fig = plt.figure()
ax1 = fig.add_subplot(411) # nrows, ncols, plot_number, top sparkline
ax1.plot(data, 'b-')
ax1.axhline(c='grey', alpha=0.5)
ax2 = fig.add_subplot(412, sharex=ax1)
ax2.plot(data, 'g-')
ax2.axhline(c='grey', alpha=0.5)
ax3 = fig.add_subplot(413, sharex=ax1)
ax3.plot(data, 'y-')
ax3.axhline(c='grey', alpha=0.5)
ax4 = fig.add_subplot(414, sharex=ax1) # bottom sparkline
ax4.plot(data, 'r-')
ax4.axhline(c='grey', alpha=0.5)
for axes in [ax1, ax2, ax3, ax4]: # remove all borders
plt.setp(axes.get_xticklabels(), visible=False)
plt.setp(axes.get_yticklabels(), visible=False)
plt.setp(axes.get_xticklines(), visible=False)
plt.setp(axes.get_yticklines(), visible=False)
plt.setp(axes.spines.values(), visible=False)
# bottom sparkline
plt.setp(ax4.get_xticklabels(), visible=True)
plt.setp(ax4.get_xticklines(), visible=True)
ax4.xaxis.tick_bottom() # but onlyt the lower x ticks not x ticks at the top
plt.tight_layout()
plt.show()
A sparkline graph is just a regular plot with all the axis removed. quite simple to do with matplotlib:
import matplotlib.pyplot as plt
import numpy as np
# create some random data
x = np.cumsum(np.random.rand(1000)-0.5)
# plot it
fig, ax = plt.subplots(1,1,figsize=(10,3))
plt.plot(x, color='k')
plt.plot(len(x)-1, x[-1], color='r', marker='o')
# remove all the axes
for k,v in ax.spines.items():
v.set_visible(False)
ax.set_xticks([])
ax.set_yticks([])
#show it
plt.show()