Python - Outputting two data sets (lists?) to data file as two columns

Question

I am very novice when it comes to python. I have done most of my programming in C++. I have a program which generates the fast Fourier transform of a data set and plots both the data and the FFT in two windows using matplotlib. Instead of plotting, I want to output the data to a file. This would be a simple task for me in C++, but I can't seem to figure this out in python. So the question is, "how can I output powerx and powery to a data file in which both data sets are in separate columns? Below is the program:

import matplotlib.pyplot as plt

from fft import fft
from fft import fft_power
from numpy import array
import math
import time


# data downloaded from ftp://ftp.cmdl.noaa.gov/ccg/co2/trends/co2_mm_mlo.txt
print ' C02 Data from Mauna Loa'
data_file_name = 'co2_mm_mlo.txt'
file = open(data_file_name, 'r')
lines = file.readlines()
file.close()
print ' read', len(lines), 'lines from', data_file_name

window = False

yinput = []
xinput = []

for line in lines :
    if line[0] != '#' :
        try:
            words = line.split()
            xval = float(words[2])
            yval = float( words[4] )
            yinput.append( yval )
            xinput.append( xval )
        except ValueError :
            print 'bad data:',line


N = len(yinput)
log2N = math.log(N, 2)
if log2N - int(log2N) > 0.0 :
    print 'Padding with zeros!'
    pads = [300.0] * (pow(2, int(log2N)+1) - N)
    yinput = yinput + pads
    N = len(yinput)
    print 'Padded : '
    print len(yinput)
    # Apply a window to reduce ringing from the 2^n cutoff
    if window : 
        for iy in xrange(len(yinput)) :
            yinput[iy] = yinput[iy] * (0.5 - 0.5 * math.cos(2*math.pi*iy/float(N-1)))

y = array( yinput ) 
x = array([ float(i) for i in xrange(len(y)) ] )
Y = fft(y)

powery = fft_power(Y)
powerx = array([ float(i) for i in xrange(len(powery)) ] )

Yre = [math.sqrt(Y[i].real**2+Y[i].imag**2) for i in xrange(len(Y))]


plt.subplot(2, 1, 1)
plt.plot( x, y )

ax = plt.subplot(2, 1, 2)
p1, = plt.plot( powerx, powery )
p2, = plt.plot( x, Yre )
ax.legend( [p1, p2], ["Power", "Magnitude"] )
plt.yscale('log')


plt.show()

Answer 1

You can use a csv.writer() to achieve this task, here is the reference: https://docs.python.org/2.6/library/csv.html

Basic usage:

zip you lists into rows:

rows=zip(powery,powerx)

Use a csv writer to write the data to a csv file:

with open('test.csv', 'wb') as f:
    writer = csv.writer(f)
    for row in rows:
        writer.writerow(row)

Answer 2

This is how you can write data from two different lists into text file in two column.

# Two random lists
index = [1, 2, 3, 4, 5]
value = [4.5, 5, 7.0, 11, 15.7]

# Opening file for output
file_name = "output.txt"
fwm = open(file_name, 'w')

# Writing data in file
for i in range(len(index)):
    fwm.write(str(index[i])+"\t")
    fwm.write(str(value[i])+"\n")

# Closing file after writing
fwm.close()

if your list contain data in the form of string then remove 'str' while writing data in file.

If you want to save data in csv file change

fwm.write(str(index[i])+"\\t")

WITH

fwm.write(str(index[i])+",")

Answer 3

Depending on what you want to use the file for, I'd suggest either the csv module or the json module.

Writing the file as CSV data will give you the ability to open it with a spreadsheet, graph it, edit it, etc.

Writing the file as JSON data will give you the ability to quickly import it into other programming languages, and to inspect it (generally read-only -- if you want to do serious editing, go with CSV).