I am using bqplot to create a live line graph on jupyter-notebook + VOILA
from bqplot import pyplot as plt2
import datetime
x_values = [] #array of datetimes
y_values = [] #array of 10+ digit numbers
plt2.show()
def functionThatIsCalledRepeatedly(x_val, y_val):
x_values.append(x_val)
y_values.append(y_val)
plt2.plot(x_values, y_values)
Part of the Resulting Plot
My question is, how do I remove the scientific notation from the y-axis. It's a simple task but I have tried a lot of things.
I tried using axes.tick_format property of the graph but I think that only works if you have axes objects which I cannot have because they require the mandatory Scale property which I cannot use because the graph is live and the x and y scales need to be generated/recalibrated while it runs.
I tried changing y_values.append(y_val) to y_values.append("{:.2f}".format(y_val)) but that converts to a string and bqplot doesn't process it as a number so it ends up with negative numbers on top of the 0 sometimes.
I tried converting to a numpy array and then doing np.set_printoptions(suppress=True) which (obviously) didn't work.
Basically tried a lot of things and I think it comes down to some bqplot property that may or may not exist. Have been stuck for a while. Thank you!
You can provide axes options with the tick format you want to the plot method:
plt2.plot(x_values, y_values, axes_options={
y=dict(tick_format='0.2f')
})
You can see examples of this axes_options (using a scatter plot, but that should work the same) in this notebook: https://github.com/bqplot/bqplot/blob/master/examples/Marks/Pyplot/Scatter.ipynb
I have a large data set (growing number of x axis), the one shown at the bottom is enough to reproduce my case. I'm trying to plot this using Pandas and matplotlib. [I'm very new with python, so apologies in advance for any mistakes.]
import os
import sys
import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_csv('test.csv', delimiter=',', index_col='Header')
df.plot(marker='s', figsize=(18,9))
plt.title("test")
plt.ylabel('y axis')
plt.xlabel('x axis')
plt.show()
sys.exit()
When I use the code above, it plots the graph, but I've got few issues.
Y axis data points looks they have been scaled (which I did not ask)
Missing few x axis data points, I understated it may not possible display all X axis values on the axis, which is fine. I was wondering would it be possible to display them on the actual data point when I move the mouse over them.
The latter is really crucial feature I'm after. My script is intended to track some data and when there is a visible bump in the plot, I need to be able to know which X values actually cause the bump. If anyone has suggestion for achieving the similar effect, they are much appreciated.
Header,header1,header2,header3,header4,header5,header6
x1,2115211,2223666,13332666,8448144,655564,366361
x2,2115213,2223666,13332666,8448144,655564,366361
x3,2115213,2223666,13332666,8448144,655564,366361
x4,2115213,2223666,13332666,8448144,655564,366361
x5,2115262,2229973,13330187,8448756,655523,366379
x6,2115262,2229973,13330187,8448756,655523,366379
x7,2115262,2229973,13330187,8448756,655523,366379
x8,2115277,2228613,13335478,8448221,655556,366362
x9,2115277,2228613,13335478,8448221,655556,366362
x10,2115211,2223666,13332666,8448144,655564,366361
x11,2115213,2223666,13332666,8448144,655564,366361
x12,2115213,2223666,13332666,8448144,655564,366361
x13,2115213,2223666,13332666,8448144,655564,366361
x14,2115213,2223666,13332666,8448144,655564,366361
x15,2115262,2229973,13330187,8448756,655523,366379
x16,2115262,2229973,13330187,8448756,655523,366379
x17,2115262,2229973,13330187,8448756,655523,366379
x18,2115277,2228613,13335478,8448221,655556,366362
x19,2115277,2228613,13335478,8448221,655556,366362
Any help is much appreciated.
I am using Python 2.7 and need to draw a time series using matplotlib library. My y axis data is numeric and everything is ok with it.
The problem is my x axis data which is not numeric, and matplotlib does not cooperate in this case. It does not draw me a time series even though it is not supposed to affect the correctness of the plot, because the x axis data is arranged by a given order anyway and it's order does not affect anything logically.
For example let's say the x data is ["i","like","python"] and the y axis data is [1,2,3].
I did not add my code because I've found that the code is ok, it works if I change the data to all numeric data.
Please explain me how can I use matplotlib to draw the time series, without making me to convert the x values to numeric stuff.
I've based my matplotlib code on following answers: How to plot Time Series using matplotlib Python, Time Series Plot Python.
Matplotlib requires someway of positioning those labels. See the following example:
import matplotlib.pyplot as plt
x = ["i","like","python"]
y = [1,2,3]
plt.plot(y,y) # y,y because both are numeric (you could create an xt = [1,2,3]
plt.xticks(y,x) # same here, the second argument are the labels.
plt.show()
, that results in this:
Notice how I've put the labels there but had to somehow say where they are supposed to be.
I also think you should put a part of your code so that it's easier for other people to suggest upon.
Consider the following code
import matplotlib.pyplot as plt
import numpy as np
time=np.arange(-100,100,01)
val =np.sin(time/10.)
time=-1.0*time
plt.figure()
plt.plot(time,val)
plt.xlim([70,-70])
plt.savefig('test.pdf')
when I open the pdf in inkscape, I can select (with F2) the entire data, it's just invisible outside of the specified xlim interval:
The problem seems to be the line
time=-1.0*time
If I omit this line, everything works perfectly.. no idea why this is. I often need such transformations because I deal with paleo-climate data which are sometimes given in year B.C. and year A.D., respectively.
The problem I see with this behavior is that someone could in principle get the data outside the range which I want to show.
Has someone a clue how to solve this problem (except for an slice of the arrays before plotting)?
I use matplotlib 1.1.1rc2
You can mask your array when plotting according to the limits you choose. Yes, this also requires changes to the code, but maybe not as extensive as you might fear. Here's an updated version of your example:
import matplotlib.pyplot as plt
import numpy as np
time=np.arange(-100,100,01)
val =np.sin(time/10.)
time=-1.0*time
plt.figure()
# store the x-limites in variables for easy multi-use
XMIN = -70.0
XMAX = 70.0
plt.plot(np.ma.masked_outside(time,XMIN,XMAX),val)
plt.xlim([XMIN,XMAX])
plt.savefig('test.pdf')
The key change is using np.ma.masked_outside for your x-axis value (note: the order of XMIN and XMAX in the mask-command is not important).
That way, you don't have to change the array time if you wanted to use other parts of it later on.
When I checked with inkscape, no data outside of the plot was highlighted.
I am a new user to the python & matplotlib, this might be a simple question but I searched the internet for hours and couldn't find a solution for this.
I am plotting precipitation data from which is in the NetCDF format. What I find weird is that, the data doesn't have any negative values in it.(I checked that many times,just to make sure). But the value in the colorbar starts with a negative value (like -0.0000312 etc). It doesnt make sense because I dont do any manipulations to the data, other that just selecting a part of the data from the big file and plotting it.
So my code doesn't much to it. Here is the code:
from mpl_toolkits.basemap import Basemap
import numpy as np
import matplotlib.pyplot as plt
from netCDF4 import Dataset
cd progs
f=Dataset('V21_GPCP.1979-2009.nc')
lats=f.variables['lat'][:]
lons=f.variables['lon'][:]
prec=f.variables['PREC'][:]
la=lats[31:52]
lo=lons[18:83]
pre=prec[0,31:52,18:83]
m = Basemap(width=06.e6,height=05.e6,projection='gnom',lat_0=15.,lon_0=80.)
x, y = m(*np.meshgrid(lo,la))
m.drawcoastlines()
m.drawmapboundary(fill_color='lightblue')
m.drawparallels(np.arange(-90.,120.,5.),labels=[1,0,0,0])
m.drawmeridians(np.arange(0.,420.,5.),labels=[0,0,0,1])
cs=m.contourf(x,y,pre,50,cmap=plt.cm.jet)
plt.colorbar()
The output that I got for that code was a beautiful plot, with the colorbar starting from the value -0.00001893, and the rest are positive values, and I believe are correct. Its just the minimum value thats bugging me.
I would like to know:
Is there anything wrong in my code? cos I know that the data is right.
Is there a way to manually change the value to 0?
Is it right for the values in the colorbar to change everytime we run the code, cos for the same data, the next time I run the code, the values go like this " -0.00001893, 2.00000000, 4.00000000, 6.00000000 etc"
I want to customize them to "0.0, 2.0, 4.0, 6.0 etc"
Thanks,
Vaishu
Yes, you can manually format everything about the colorbar. See this:
import matplotlib.colors as mc
import matplotlib.pyplot as plt
plt.imshow(X, norm=mc.Normalize(vmin=0))
plt.colorbar(ticks=[0,2,4,6], format='%0.2f')
Many plotting functions including imshow, contourf, and others include a norm argument that takes a Normalize object. You can set the vmin or vmax attributes of that object to adjust the corresponding values of the colorbar.
colorbar takes the ticks and format arguments to adjust which ticks to display and how to display them.