Plotting 2 arrays against another on one graph

Question

I want to compare how two independent variables vary with time, by plotting both of them on the one graph. All three variables are in the form of arrays, which I pulled from a text file. This is what I have got so far:

from pylab import *

data_ = []

with open('all_the_data.txt') as dat_:
    for line in dat_:
        data_.append([i for i in line.split()])

D = zip(*data_)

def f1(t):
    y = D[1]
    return y

def f2(t):
    y = D[2]
    return y

if __name__ == '__main__':
    t = D[0]
    A = f1
    B = f2
    plot(t, A, 'bo')
    hold('on')
    plot(t, B, 'gX')
    xlabel('timestamp (unix)')
    ylabel('Station population')
    legend('Station 1','Station 2')
    title('Variance of Stations 1 and 2')
    show()
    savefig('2_stations_vs_time.png')

Problem is, it isn't working, and i don't know why. I got it from a tutorial on graphing two functions.

Answer 1

We plot the data not the function. So pass A, B is wrong. I think what you need to do is:

from pylab import *

data_ = []

with open('all_the_data.txt') as dat_:
    for line in dat_:
        data_.append([i for i in line.split()])

D = zip(*data_)

if __name__ == '__main__':
    t = D[0]
    A = D[1]
    B = D[2]
    plot(t, A, 'bo')
    hold('on')
    plot(t, B, 'gX')
    xlabel('timestamp (unix)')
    ylabel('Station population')
    legend('Station 1','Station 2')
    title('Variance of Stations 1 and 2')
    show()
    savefig('2_stations_vs_time.png')

I have tested if your D is a right value, for example D = [list(range(100)), list(range(10, 110)), list(range(20, 120))]. The code works well.

Answer 2

Edit: I think the problem may be with how you extract the data. When you call A=f1 and B=f2, you should write A=f1(t) and B=f2(t) to conform with the way you've constructed f1 and f2. However, why do it that way?

with open('all_the_data.txt', 'r') as dat_:
    for line in dat_:
        data_.append([i for i in line.strip().split()])

D = zip(*data_)
t = D[0]
A = D[1]
B = D[2]

For plotting, I prefer the object oriented approach.

import matplotlib.pyplot as plt
f = plt.figure()
ax = f.add_subplot(111)
ax.plot(t, A, 'bo', label="Station 1")
ax.plot(t, B, 'gX', label="station 2")
ax.legend()

ax.set_xlabel('timestamp (unix)')
ax.set_ylabel('Station population')
ax.set_title('Variance of Stations 1 and 2')

f.savefig('2_stations_vs_time.png')