How to plot cdf in matplotlib in Python?

Question

I have a disordered list named d that looks like:

[0.0000, 123.9877,0.0000,9870.9876, ...]

I just simply want to plot a cdf gr

Answer 1

The numpy function to compute cumulative sums cumsum can be useful here

In [1]: from numpy import cumsum
In [2]: cumsum([.2, .2, .2, .2, .2])
Out[2]: array([ 0.2,  0.4,  0.6,  0.8,  1. ])

Answer 2

For an arbitrary collection of values, x:

def cdf(x, plot=True, *args, **kwargs):
    x, y = sorted(x), np.arange(len(x)) / len(x)
    return plt.plot(x, y, *args, **kwargs) if plot else (x, y)

((If you're new to python, the *args, and **kwargs allow you to pass arguments and named arguments without declaring and managing them explicitly))

Answer 3

As mentioned, cumsum from numpy works well. Make sure that your data is a proper PDF (ie. sums to one), otherwise the CDF won't end at unity as it should. Here is a minimal working example:

import numpy as np
from pylab import *

# Create some test data
dx = 0.01
X  = np.arange(-2, 2, dx)
Y  = exp(-X ** 2)

# Normalize the data to a proper PDF
Y /= (dx * Y).sum()

# Compute the CDF
CY = np.cumsum(Y * dx)

# Plot both
plot(X, Y)
plot(X, CY, 'r--')

show()

Answer 4

import matplotlib.pyplot as plt
X=sorted(data)
Y=[]
l=len(X)
Y.append(float(1)/l)
for i in range(2,l+1):
    Y.append(float(1)/l+Y[i-2])
plt.plot(X,Y,color=c,marker='o',label='xyz')

I guess this would do,for the procedure refer http://www.youtube.com/watch?v=vcoCVVs0fRI

Answer 5

I know I'm late to the party. But, there is a simpler way if you just want the cdf for your plot and not for future calculations:

plt.hist(put_data_here, normed=True, cumulative=True, label='CDF',
         histtype='step', alpha=0.8, color='k')

As an example,

plt.hist(dataset, bins=bins, normed=True, cumulative=True, label='CDF DATA', 
         histtype='step', alpha=0.55, color='purple')
# bins and (lognormal / normal) datasets are pre-defined

EDIT: This example from the matplotlib docs may be more helpful.