Simple question and I tried a quick search before posting but could not find. I am trying to do a chart and axis Y consists of price.
However Y is scaled like attached image and has only 1 decimal. How do I make y axis more precise with 2 decimals and more entries with increment of 0.01?
::Update with code::
# Make the plot
fig, ax = plt.subplots(figsize=(48,32))
ax.scatter(x=times, y=tidy['Price'], c=colors, s=tidy['Volume'] / 4000, alpha=0.4)
ax.ticklabel_format(axis='y', style='plain')
ax.set(
xlabel='Time',
xlim=(xmin, xmax),
ylabel='Price'
)
ax.xaxis.set_major_formatter(DateFormatter('%H:%M'))
One method to increase the number of decimals is to use a formatter for your axis:
from matplotlib.ticker import FormatStrFormatter
ax.yaxis.set_major_formatter(FormatStrFormatter('%.2f'))
However, this method will not increase the number of ticks on your axis. You can set the yticks with .01 increments using the following but you might end up over-saturating the axis might want to increase the increment size.
ax.set_yticks(np.arange(108.30,108.71,.01))
Related
I am working on drawing lineplots with matplotlib.
I checked several posts and could understand how the line break works on matplotlib (Break // in x axis of matplotlib)
However, I was wondering is it possible to break x and y axis all together at the same time.
My current drawing looks like below.
As shown on the graph, x-axis [2000,5000] waste spaces a lot.
Because I have more data that need to be drawn after 7000, I want to save more space.
Is it possible to split x-axis together with y-axis?
Or is there another convenient way to not to show specific region on lineplot?
If there is another library enabling this, I am willing to drop matplotlib and adopt others...
Maybe splitting the axis isn't your best choice. I would perhaps try inserting another smaller figure into the open space of your large figure using add_axes(). Here is a small example.
t = np.linspace(0, 5000, 1000) # create 1000 time stamps
data = 5*t*np.exp(-t/100) # and some fake data
fig, ax = plt.subplots()
ax.plot(t, data)
box = ax.get_position()
width = box.width*0.6
height = box.height*0.6
x = 0.35
y = 0.35
subax = fig.add_axes([x,y,width,height])
subax.plot(t, data)
subax.axis([0, np.max(t)/10, 0, np.max(data)*1.1])
plt.show()
I generate plots like below:
from pylab import *
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker
import matplotlib.ticker as ticker
rcParams['axes.linewidth'] = 2 # set the value globally
rcParams['font.size'] = 16# set the value globally
rcParams['font.family'] = ['DejaVu Sans']
rcParams['mathtext.fontset'] = 'stix'
rcParams['legend.fontsize'] = 24
rcParams['axes.prop_cycle'] = cycler(color=['grey','b','g','r','orange'])
rc('lines', linewidth=2, linestyle='-',marker='o')
rcParams['axes.xmargin'] = 0
rcParams['axes.ymargin'] = 0
t = arange(0,21,1)
v = 2.0
s = v*t
plt.figure(figsize=(12, 4))
plt.plot(t,s,label='$s=%1.1f\cdot t$'%v)
plt.title('Wykres drogi w czasie $s=v\cdot t$')
plt.xlabel('Czas $t$, s')
plt.ylabel('Droga $s$, m')
plt.autoscale(enable=True, axis='both', tight=None)
legend(loc='best')
plt.xlim(min(t),max(t))
plt.ylim(min(s),max(s))
plt.grid()
plt.show()
When I am changing the value t = arange(0,21,1) for example to t = arange(0,20,1) which gives me for example on the x axis max value= 19.0 my max value dispirs from the x axis. The same situation is of course with y axis.
My question is how to force matplotlib to produce always plots where on the axes are max values just at the end of the axes like should be always for my purposes or should be possible to chose like an option?
Imiage from my program in Fortan I did some years ago
Matplotlib is more efficiens that I use it but there should be an opition like that (the picture above).
In this way I can always observe max min in text windows or do take addiional steps to make sure about max min values. I would like to read them from axes and the question is ...Are there such possibilites in mathplotlib ??? If not I will close the post.
Axes I am thinking about more or less
I see two ways to solve the problem.
Set the axes automatic limit mode to round numbers
In the rcParams you can do this with
rcParams['axes.autolimit_mode'] = 'round_numbers'
And turn off the manual axes limits with min and max
plt.xlim(min(t),max(t))
plt.ylim(min(s),max(s))
This will produce the image below. Still, the extreme values of the axes are shown at the nearest "round numbers", but the user can approximately catch the data range limits. If you need the exact value to be displayed, you can see the second solution which cannot be directly used from the rcParams.
or – Manually generate axes ticks
This solution implies explicitly asking for a given number of ticks. I guess there is a way to automatize it depending on the axes size etc. But if you are dealing with more or less every time the same graph size, you can decide a fixed number of ticks manually. This can be done with
plt.xlim(min(t),max(t))
plt.ylim(min(s),max(s))
plt.xticks(np.linspace(t.min(), t.max(), 7)) # arbitrary chosen
plt.yticks(np.linspace(s.min(), s.max(), 5)) # arbitrary chosen
generated the image below, quite similar to your image example.
I am struggling to 'translate' the instructions I find for Python to the use of Pyplot in Julia. This must be a simple question, but do you know how to set the number of ticks in a plot in Julia using Pyplot?
If you have
x = [1,2,3,4,5]
y = [1,3,6,8,11]
you can
PyPlot.plot(x,y)
which draws the plot
and then do
PyPlot.xticks([1,3,5])
for tics at 1,3 and 5 on the x-axis
PyPlot.yticks([1,6,11])
for tics at 1,6 and 11 on the y-axis
Tic spacing
if you want fx 4 tics and want it evenly spaced and dont mind Floats, you can do
collect(linspace(x[1], x[end], 4).
If you need the tics to be integers and you want 4 tics, you can do
collect(x[1]:div(x[end],4):x[end])
Edit
Maybe this wont belong here but atleast you'll see it...
whenever you're looking for a method that's supposed to be in a module X you can find these methods by typing in the REPL X. + TAB key
to clarify, if you want to search a module for a method you suspect starts with an x, like xticts, in the REPL (terminal/shell) do
PyPlot.x
and press TAB twice and you'll see
julia> PyPlot.x
xkcd xlabel xlim xscale xticks
and if you're not sure exactly how the method works, fx its arguments, and there isnt any help available, you can call
methods(PyPlot.xticks)
to see every "version" that method has
Bonus
The module for all the standard methods, like maximum, vcat etc is Base
After some trying and searching, I found a way to do it. One can just set the number of bins that should be on each axis. Here is a minimal example:
using PyPlot
x = linspace(0, 10, 200)
y = sin(x)
fig, ax = subplots()
ax[:plot](x, y, "r-", linewidth=2, label="sine function", alpha=0.6)
ax[:legend](loc="upper center")
ax[:locator_params](axis ="y", nbins=4)
The last line specifies the number of bins that should be used on the y-axis. Leaving the argument axis unspecified will set that option for both axis at the same value.
in plotting the data some times there are a few very large (or very small) numbers which, if not taken care of, will affect the contour in a bad way. a solution is to take out the 10% highest and lowest data out of the contour color grading and considering them as less than and more than. the following figure shows the idea:
the two arrow shapes on the top and the bottom of the bar support this idea. any value above 14 will be shown in white and any value below -2 will be shown in black color. how is it possible in matplotlib?
How can I define:
- to put the 5% of highest values and 5% of lowest values in two categories shown in the triangular parts in both ends of the bar? (Should I define it the contour operation or are there other ways?)
- what if I want to give certain values instead of the percentage? for instance, ask to put any value above 14 on the white triangule and any value below -2 as black areas?
Thank you so much for your help.
Taken from http://matplotlib.org/examples/api/colorbar_only.html. You can play with it and you will see if it could solve your problem.
import matplotlib.pyplot as plt
from matplotlib import mpl
import numpy as np
x = np.linspace(-1,1,100)
X,Y = np.meshgrid(x,x)
Z = np.exp(-X**2-Y**2)
vmin = 0.3 #Lower value
vmax = 0.9 #Upper value
bounds = np.linspace(vmin,vmax,4)
cmap = mpl.colors.ListedColormap([(0,0,0),(0.5,0.5,0.5),(0,1,0),(1,1,1)])
norm = mpl.colors.BoundaryNorm(bounds, cmap.N)
plt.imshow(Z,cmap=cmap,interpolation='nearest',vmin=vmin,vmax=vmax)
ax = plt.colorbar().ax
cb = mpl.colorbar.ColorbarBase(ax, norm=norm,
extend='both',
cmap=cmap)
cmap.set_over([0,0,1])
cmap.set_under([1,0,0])
plt.show()
I'm drawing the bloxplot shown below using python and matplotlib. Is there any way I can reduce the distance between the two boxplots on the X axis?
This is the code that I'm using to get the figure above:
import matplotlib.pyplot as plt
from matplotlib import rcParams
rcParams['ytick.direction'] = 'out'
rcParams['xtick.direction'] = 'out'
fig = plt.figure()
xlabels = ["CG", "EG"]
ax = fig.add_subplot(111)
ax.boxplot([values_cg, values_eg])
ax.set_xticks(np.arange(len(xlabels))+1)
ax.set_xticklabels(xlabels, rotation=45, ha='right')
fig.subplots_adjust(bottom=0.3)
ylabels = yticks = np.linspace(0, 20, 5)
ax.set_yticks(yticks)
ax.set_yticklabels(ylabels)
ax.tick_params(axis='x', pad=10)
ax.tick_params(axis='y', pad=10)
plt.savefig(os.path.join(output_dir, "output.pdf"))
And this is an example closer to what I'd like to get visually (although I wouldn't mind if the boxplots were even a bit closer to each other):
You can either change the aspect ratio of plot or use the widths kwarg (doc) as such:
ax.boxplot([values_cg, values_eg], widths=1)
to make the boxes wider.
Try changing the aspect ratio using
ax.set_aspect(1.5) # or some other float
The larger then number, the narrower (and taller) the plot should be:
a circle will be stretched such that the height is num times the width. aspect=1 is the same as aspect=’equal’.
http://matplotlib.org/api/axes_api.html#matplotlib.axes.Axes.set_aspect
When your code writes:
ax.set_xticks(np.arange(len(xlabels))+1)
You're putting the first box plot on 0 and the second one on 1 (event though you change the tick labels afterwards), just like in the second, "wanted" example you gave they are set on 1,2,3.
So i think an alternative solution would be to play with the xticks position and the xlim of the plot.
for example using
ax.set_xlim(-1.5,2.5)
would place them closer.
positions : array-like, optional
Sets the positions of the boxes. The ticks and limits are automatically set to match the positions. Defaults to range(1, N+1) where N is the number of boxes to be drawn.
https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.boxplot.html
This should do the job!
As #Stevie mentioned, you can use the positions kwarg (doc) to manually set the x-coordinates of the boxes:
ax.boxplot([values_cg, values_eg], positions=[1, 1.3])