I am trying to plot two separate quantities on the same graph using twiny as follows:
fig = figure()
ax = fig.add_subplot(111)
ax.plot(T, r, 'b-', T, R, 'r-', T, r_geo, 'g-')
ax.set_yscale('log')
ax.annotate('Approx. sea level', xy=(Planet.T_day*1.3,(Planet.R)/1000), xytext=(Planet.T_day*1.3, Planet.R/1000))
ax.annotate('Geostat. orbit', xy=(Planet.T_day*1.3, r_geo[0]), xytext=(Planet.T_day*1.3, r_geo[0]))
ax.set_xlabel('Rotational period (hrs)')
ax.set_ylabel('Orbital radius (km), logarithmic')
ax.set_title('Orbital charts for ' + Planet.N, horizontalalignment='center', verticalalignment='top')
ax2 = ax.twiny()
ax2.plot(v,r,'k-')
ax2.set_xlabel('Linear speed (ms-1)')
show()
and the data is presented fine, but I am having the problem that the figure title is overlapping with the axes labels on the secondary x axis so that it's barely legible (I wanted to post a picture example here, but I don't have a high enough rep yet).
I'd like to know if there's a straightforward way to just shift the title directly up a few tens of pixels, so that the chart looks prettier.
I'm not sure whether it is a new feature in later versions of matplotlib, but at least for 1.3.1, this is simply:
plt.title(figure_title, y=1.08)
This also works for plt.suptitle(), but not (yet) for plt.xlabel(), etc.
Forget using plt.title and place the text directly with plt.text. An over-exaggerated example is given below:
import pylab as plt
fig = plt.figure(figsize=(5,10))
figure_title = "Normal title"
ax1 = plt.subplot(1,2,1)
plt.title(figure_title, fontsize = 20)
plt.plot([1,2,3],[1,4,9])
figure_title = "Raised title"
ax2 = plt.subplot(1,2,2)
plt.text(0.5, 1.08, figure_title,
horizontalalignment='center',
fontsize=20,
transform = ax2.transAxes)
plt.plot([1,2,3],[1,4,9])
plt.show()
I was having an issue with the x-label overlapping a subplot title; this worked for me:
import matplotlib.pyplot as plt
fig, ax = plt.subplots(2, 1)
ax[0].scatter(...)
ax[1].scatter(...)
plt.tight_layout()
.
.
.
plt.show()
before
after
reference:
https://matplotlib.org/users/tight_layout_guide.html
ax.set_title('My Title\n', fontsize="15", color="red")
plt.imshow(myfile, origin="upper")
If you put '\n' right after your title string, the plot is drawn just below the title. That might be a fast solution too.
You can use pad for this case:
ax.set_title("whatever", pad=20)
Just use plt.tight_layout() before plt.show(). It works well.
A temporary solution if you don't want to get into the x, y position of your title.
Following worked for me.
plt.title('Capital Expenditure\n') # Add a next line after your title
kudos.
Using the plt.tight_layout() before the plt.show() works for me well.
you can even make it better and visible by adding a padding
ax.set_title("title", pad=15)
Related
I am trying to plot two separate quantities on the same graph using twiny as follows:
fig = figure()
ax = fig.add_subplot(111)
ax.plot(T, r, 'b-', T, R, 'r-', T, r_geo, 'g-')
ax.set_yscale('log')
ax.annotate('Approx. sea level', xy=(Planet.T_day*1.3,(Planet.R)/1000), xytext=(Planet.T_day*1.3, Planet.R/1000))
ax.annotate('Geostat. orbit', xy=(Planet.T_day*1.3, r_geo[0]), xytext=(Planet.T_day*1.3, r_geo[0]))
ax.set_xlabel('Rotational period (hrs)')
ax.set_ylabel('Orbital radius (km), logarithmic')
ax.set_title('Orbital charts for ' + Planet.N, horizontalalignment='center', verticalalignment='top')
ax2 = ax.twiny()
ax2.plot(v,r,'k-')
ax2.set_xlabel('Linear speed (ms-1)')
show()
and the data is presented fine, but I am having the problem that the figure title is overlapping with the axes labels on the secondary x axis so that it's barely legible (I wanted to post a picture example here, but I don't have a high enough rep yet).
I'd like to know if there's a straightforward way to just shift the title directly up a few tens of pixels, so that the chart looks prettier.
I'm not sure whether it is a new feature in later versions of matplotlib, but at least for 1.3.1, this is simply:
plt.title(figure_title, y=1.08)
This also works for plt.suptitle(), but not (yet) for plt.xlabel(), etc.
Forget using plt.title and place the text directly with plt.text. An over-exaggerated example is given below:
import pylab as plt
fig = plt.figure(figsize=(5,10))
figure_title = "Normal title"
ax1 = plt.subplot(1,2,1)
plt.title(figure_title, fontsize = 20)
plt.plot([1,2,3],[1,4,9])
figure_title = "Raised title"
ax2 = plt.subplot(1,2,2)
plt.text(0.5, 1.08, figure_title,
horizontalalignment='center',
fontsize=20,
transform = ax2.transAxes)
plt.plot([1,2,3],[1,4,9])
plt.show()
I was having an issue with the x-label overlapping a subplot title; this worked for me:
import matplotlib.pyplot as plt
fig, ax = plt.subplots(2, 1)
ax[0].scatter(...)
ax[1].scatter(...)
plt.tight_layout()
.
.
.
plt.show()
before
after
reference:
https://matplotlib.org/users/tight_layout_guide.html
ax.set_title('My Title\n', fontsize="15", color="red")
plt.imshow(myfile, origin="upper")
If you put '\n' right after your title string, the plot is drawn just below the title. That might be a fast solution too.
You can use pad for this case:
ax.set_title("whatever", pad=20)
Just use plt.tight_layout() before plt.show(). It works well.
A temporary solution if you don't want to get into the x, y position of your title.
Following worked for me.
plt.title('Capital Expenditure\n') # Add a next line after your title
kudos.
Using the plt.tight_layout() before the plt.show() works for me well.
you can even make it better and visible by adding a padding
ax.set_title("title", pad=15)
I have found similar questions previously, but I haven't managed to find an answer that has worked for me.
I am plotting directly from my data frame and would like to label my axis. This is the code I am using:
fig,ax = plt.subplots()
ax = plt.gca()
ax.set_xlabel("Time (s)")
ax.set_ylabel("Normalised Vertical Acceleration")
data.plot(kind='line', x='time', y='accel_y', ax=ax)
The graph generated only has "cycle" as the x-axis label and no y-axis label. Is there something that I'm doing wrong? Or is there a better method?
Thanks in advance.
Edited answer: Based on your updated question
You don't need additionally ax = plt.gca(). Then, first plot the data and then set the axis labels
fig, ax = plt.subplots()
data.plot(kind='line', x='time', y='accel_y', ax=ax)
ax.set_xlabel("Time (s)")
ax.set_ylabel("Normalised Vertical Acceleration")
#Sheldore's answer didn't work for me.
Instead, we need to use the inbuild function parameter:
fig, ax = plt.subplots()
data.plot(kind='line', x='time', y='accel_y', ax=ax,
ylabel="Normalised Vertical Acceleration",
xlabel="Time (s)")
I would report this as a bug to Pandas, which might be version-specific.
I am using matplotlib.pyplot to plot some graphs and for some reasons I can't see the lines of the axes, although I can see the xticks and yticks. Important to note that I am using python notebook, and usually I try to visualize my graphs with the function (%matplotlib inline)
Here is an example figure that I get (without the axes):
Here is the code I used to produce this figure:
fig, ax = plt.subplots(1,1, figsize=(7.5,6), sharey=False, sharex=False, edgecolor='k', frameon=True)
ax.plot(np.array(frequency_vec), before_LTP, 'b-o', label='Before');
ax.plot(np.array(frequency_vec), After_LTP, 'r-o', label='After');
plt.yticks([1,2,3,4,5,6,7,8], ['1','2','3','4','5','6','7','0'], fontsize=14)
plt.xticks(fontsize=14)
plt.rcParams['axes.edgecolor']='k'
ax.patch.set_visible(False)
ax.grid(False)
ax.set_frame_on(True)
ax.set_xlim(0, 110)
ax.set_ylim(1,(Number_of_pulses)+2)
ax.legend(loc='best', fontsize=15)
plt.xticks([12.5,25,50,75,100], ['12.5','25','50','75','100']);
So again - How can I make my axes-lines to be visible?
Thanks!
Do you have some special setting in your matplotlibrc file such as edgecolor?
import matplotlib as mpl
print mpl.rcParams['axes.edgecolor']
If it's 'w' (white) set it to 'k' (black)
If it's not edgecolor, do you have frameon = False? Try something like this:
fig, ax = subplots()
ax.plot([1,2,4],[4,5,6], 'r^-')
ax.set_frame_on(True)
I wrote that and it worked
plt.axes().get_xaxis().set_visible(False)
plt.axes().get_yaxis().set_visible(False)
Well, just write 'True' instead of 'False'.
x = ['01-02', '02-02', '03-02', '04-02', '05-02']
y = [2, 2, 3, 7, 2]
fig, ax = plt.subplots(1, 1)
ax.bar(range(len(y)), y, width=0.3,align='center',color='skyblue')
plt.xticks(range(len(y)), x, size='small')
plt.savefig('/home/user/graphimages/foo2.png')
plt.close()
I want to draw grid lines (of x & y) behind the bar graph.
To add a grid you simply need to add
ax.grid()
If you want the grid to be behind the bars then add
ax.grid(zorder=0)
ax.bar(range(len(y)), y, width=0.3, align='center', color='skyblue', zorder=3)
The important part is that the zorder of the bars is greater than grid. Experimenting it seems zorder=3 is the lowest value that actually gives the desired effect. I have no idea why zorder=1 isn't sufficient.
EDIT:
I have noticed this question has already been answered here using a different method although it suffers some link rot. Both methods yield the same result as far as I can see but andrew cooke's answer is more elegant.
I am suggesting another solution since the most voted answer did not work for me. You can use the following code to set the gridlines behind the plot.
ax.set_axisbelow(True)
ax.grid(color='gray', linestyle='dashed')
I got this code from this answer.
plt.grid(True, color = "grey", linewidth = "1.4", linestyle = "-.")
This worked for me, the grid lines will be in grey border color,if you want can change border design to linestyle = ".."
Like this
plt.grid(True, color = "grey", linewidth = "1.4", linestyle = "..")
Summing up entire code block:
fig, ax = plt.subplots(1, 1)
ax.bar(range(len(y)), y, width=0.3,align='center',color='skyblue')
plt.xticks(range(len(y)), x, size='small')
plt.grid(True, color = "grey", linewidth = "1.4", linestyle = "-.")
plt.savefig('/home/user/graphimages/foo2.png')
plt.close()
use .grid() it makes the order go to 0 (back)
ax.grid(zorder=0)
ax.grid(zorder=0) Woud work. But First Place the Bar and then Place the Grid.Not the orther way.
ax = df.plot.bar(x='Index', y='Values', rot=90)
ax.grid(zorder=0)
I took some currency Correlation with Year and Sorted it as my Data Frame df, and below is the result of the code run.
I need to add a semi transparent skin over my matplotlib figure. I was thinking about adding a rectangle to the figure with alpha <1 and a zorder high enough so its drawn on top of everything.
I was thinking about something like that
figure.add_patch(Rectangle((0,0),1,1, alpha=0.5, zorder=1000))
But I guess rectangles are handled by Axes only. is there any turn around ?
Late answer for others who google this.
There actually is a simple way, without phantom axes, close to your original wish. The Figure object has a patches attribute, to which you can add the rectangle:
fig, ax = plt.subplots(nrows=1, ncols=1)
ax.plot(np.cumsum(np.random.randn(100)))
fig.patches.extend([plt.Rectangle((0.25,0.5),0.25,0.25,
fill=True, color='g', alpha=0.5, zorder=1000,
transform=fig.transFigure, figure=fig)])
Gives the following picture (I'm using a non-default theme):
The transform argument makes it use figure-level coordinates, which I think is what you want.
You can use a phantom axes on top of your figure and change the patch to look as you like, try this example:
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_axes([0,0,1,1])
ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)
ax.set_zorder(1000)
ax.patch.set_alpha(0.5)
ax.patch.set_color('r')
ax2 = fig.add_subplot(111)
ax2.plot(range(10), range(10))
plt.show()
If you aren't using subplots, using gca() will work easily.
from matplotlib.patches import Rectangle
fig = plt.figure(figsize=(12,8))
plt.plot([0,100],[0,100])
plt.gca().add_patch(Rectangle((25,50),15,15,fill=True, color='g', alpha=0.5, zorder=100, figure=fig))