I want to plot some data. The first column contains the x-data. But matplotlib doesn't plot this. Where is my mistake?

```
import numpy as np
from numpy import cos
from scipy import *
from pylab import plot, show, ylim, yticks
from matplotlib import *
from pprint import pprint
n1 = 1.0
n2 = 1.5
#alpha, beta, intensity
data = [
[10, 22, 4.3],
[20, 42, 4.2],
[30, 62, 3.6],
[40, 83, 1.3],
[45, 102, 2.8],
[50, 123, 3.0],
[60, 143, 3.2],
[70, 163, 3.8],
]
for i in range(len(data)):
rhotang1 = (n1 * cos(data[i][0]) - n2 * cos(data[i][1]))
rhotang2 = (n1 * cos(data[i][0]) + n2 * cos(data[i][1]))
rhotang = rhotang1 / rhotang2
data[i].append(rhotang) #append 4th value
pprint(data)
x = data[:][0]
y1 = data[:][2]
y3 = data[:][3]
plot(x, y1, x, y3)
show()
```

EDIT: http://paste.pocoo.org/show/205534/ But it doesn't work.

```
x = data[:][0]
y1 = data[:][2]
y3 = data[:][3]
```

These lines don't do what you think.

First they take a slice of the array which is the whole array (that is, just a copy), then they pull out the 0th, 2nd or 3rd ROW from that array, not column.

You could try

```
x = [row[0] for row in x]
```

etc.

You can do this by converting data to a numpy array:

```
data = np.array(data) # insert this new line after your appends
pprint(data)
x = data[:,0] # use the multidimensional slicing notation
y1 = data[:,2]
y3 = data[:,3]
plot(x, y1, x, y3)
```

A few additional points:

You can do the calculation in a more clear and vectorized way using numpy, like this

```
data = np.array(data)
rhotang1 = n1*cos(data[:,0]) - n2*cos(data[:,1])
rhotang2 = n1*cos(data[:,0]) + n2*cos(data[:,1])
y3 = rhotang1 / rhotang2
```

As you wrote it, your calculation may not give what you want since `cos`

etc take radians as their inputs and your numbers look like degrees.

Licensed under: CC-BY-SA with attribution

Not affiliated with: Stack Overflow