I'm quite new to python and I need some help. I would like to plot errorbars equivalent to 1sigma standard deviations on my plot as the 16th and 84th percentile values of the distributions. I tried with (using matplotlib):
err=np.std(x)
but it just gives me the standard deviations.
Thanks.
If you want vertical error bars
ax = plt.gca()
ax.errorbar(x, y, yerr=np.vstack([error_low, error_high]))
plt.draw()
where error_low and error_high are 1D sequences of the same length an x and y. The error bars are drawn at y[i] - error_low[i] and y[i] + error_high[i].
matplotlib just draws what you tell it to, it is your job to provide the semantics.
errorbar documentation
Related
Hey so I'm an undergraduate working in an imaging lab and I have a 3D numpy array that has values from 0-9 to indicate concentration in a 3D space. I'm trying to plot these values in a scatterplot with a colormap to indicate the value between 0-9. The array is 256 x 256 x 48, so I feel like the size of it is making it difficult for me to plot the array in a meaningful way.
I've attached a picture of what it looks like right now. As you can see the concentration looks very "faded" even for very high values and I'm not entirely sure why. Here is the code I'm using to generate the plot:
current heatmap
fig = plt.figure()
x, y, z = np.meshgrid(range(256), range(256), range(48))
col = sum_array.flatten()
ax = fig.add_subplot(111, projection = '3d')
sc = ax.scatter(x, y, z, c = col, cmap='Reds',
linewidths=.01, s=.03, vmin=0, vmax=9,
marker='.', alpha=1)
plt.colorbar(sc)
plt.show()
If anyone can help me display the colors in a more bright/concentrated manner so the heat map is visually useful, I'd really appreciate it. Thank you!
the image of what I mean in my question
I'm using BMP280 to measure Temperature and Pressure using Raspberry.
I'm using matplotlib to make a graph, but the matplotlib simplify my Y axis bi adding +9.967e2.
is there any way to avoid matplotlib simplify my Y axis. Sorry I'm new to this so I don't know much.
I tried to search in google but I don't find anything. Maybe I'm using the wrong keyword as I don't know what should I search.
You can turn off the offset as shown in the examples here. For example, if you've made you plot with:
from matplotlib import pyplot as plt
plt.plot(x, y)
then you can turn off the offset with
ax = plt.gca() # get the axes object
# turn off the offset (on the y-axis only)
ax.ticklabel_format(axis="y", useOffset=False)
plt.show()
See the ticklabel_format docs for more info.
I am trying to visualize some data and have built a scatter plot with this code -
sns.regplot(y="Calls", x="clientid", data=Drop)
This is the output -
I don't want it to consider the x-axis. I just want to see how the data lie w.r.t y-axis. Is there a way to do that?
As #iayork suggested, you can see the distribution of your points with a striplot or a swarmplot (you could also combine them with a violinplot). If you need to move the points closer to the y-axis, you can simply adjust the size of the figure so that the width is small compared to the height (here i'm doing 2 subplots on a 4x5 in figure, which means that each plot is roughly 2x5 in).
fig, (ax1,ax2) = plt.subplots(1,2, figsize=(4,5))
sns.stripplot(d, orient='vert', ax=ax1)
sns.swarmplot(d, orient='vert', ax=ax2)
plt.tight_layout()
However, I'm going to suggest that maybe you want to use distplot instead. This function is specifically created to show the distribution of you data. Here i'm plotting the KDE of the data, as well as the "rugplot", which shows the position of the points along the y-axis:
fig = plt.figure()
sns.distplot(d, kde=True, vertical=True, rug=True, hist=False, kde_kws=dict(shade=True), rug_kws=dict(lw=2, color='orange'))
My question is simple.Hot to make the two scatter plot in one figure?
There is error if I just write the two pl.scatter one by one.
a,b,c=np.loadtxt('mydata',usecols=(0,1,2),delimiter=",",unpack=True)
pl.scatter(a,b,color='g',s=0.5,'b')
pl.scatter(b,c,'r')
The other question is how to use the left y and right y axis together,say,the first scatter plot use the left y axis and,the second scatter plot use the right y axis.
You can use ax.twinx() to create a second y-axis that shares the same x-axis
ax1 = pl.axes()
ax2 = ax1.twinx()
ax1.scatter(a,b,color='g',s=0.5)
ax2.scatter(b,c,color='r')
The error you were seeing is probably because you have a non-keyword argument ('b') after a keyword argument (color='r').
Can I have both twinx and twiny together (i.e. something like twinxy)?
I want to put a CDF on a bar plot where the X axis of the bar plot is in log-scale. I cannot make the Ys together, because the bar plot y range is very large comparing [0,1] for CDF.
Any ideas?
Thanks,
If I understand your question right, you want to plot two things on the same axes with no shared axis. There is probably a better way to do this, but you can stack twinx (doc) and twiny (doc) as such
ax # your first axes
ax_new = ax.twinx().twiny()
Which will give you tick marks on all sides of the plot. ax will plot against the bottom and left, ax_new will plot against the top and right.