How would I split these data in to two separate lists to plot in python?

Sticking to the basics:

fil = open("big_text_file.txt")
list1 = []
list2 = []
text = fil.readline()
while text:
    try:
        nums = text.split()
        list1.append(float(nums[0]))
        list2.append(float(nums[1]))
    except:
        pass
    text = fil.readline()

print(list1)
print(list2)

Explanation:

• create two lists
• As you said it is a big text file (so reading line by line)
• splitting the line read on space " " (Single Space is default in split)
• If the above fails means empty line. (That's what try and except are for)
• update the two lists (if no error)
• read next line.

Output:

[397.451, 397.585, 397.719, 397.853, 397.987, 398.121, 398.256, 398.39, 398.524, 398.658, 398.792, 398.926, 399.06, 399.194, 399.328, 399.463, 399.597, 399.731, 399.865, 399.999]
[-48.38, -48.38, -48.38, -18.38, -3.38, 6.62, -0.38, -1.38, 7.62, 4.62, -4.38, 12.62, 5.62, -6.38, -6.38, 0.62, -6.38, -12.38, 1.62, 2.62]

Use the csv library: https://docs.python.org/3/library/csv.html

Solution:

import csv

with open("spectroscopy.txt", newline="") as csvfile:
    reader = csv.reader(csvfile, delimiter=" ")
    column_A = []
    column_B = []
    for row in reader:
        try:
            column_A.append(float(row[0]))
            column_B.append(float(row[1]))
        except ValueError:
            pass

Alternative with pandas:

import pandas as pd

data = pd.read_csv("spectroscopy.txt", sep=" ", header=None, index_col=0)

spect_list = []

spect_list_a =[]

spect_list_b =[]

with open('spect.txt') as f:
    for i in  f.readlines():            #read entire file as lines
        i = (i.rstrip('\n'))        #remove newlin character
        if i:                       #discard blank lines
            spect_list.append(i)
            spect_list_a.append(i.split()[0])
            spect_list_b.append(i.split()[1])
                 
print(spect_list)
print(spect_list_a)
print(spect_list_b)

you get python list with element as 'element' (with quotes) not sure is the right answer

got it :

use

spect_list_a.append(float(i.split()[0]))
spect_list_b.append(float(i.split()[1]))

Using a transposition trick and a parameter to auto-convert the columns to float. Also, skipinitialspace handles a couple of lines with two spaces between the values.

import csv

# The quoting value auto-converts numeric columns to float.
with open('input.csv',newline='') as f:
    r = csv.reader(f,delimiter=' ',quoting=csv.QUOTE_NONNUMERIC,skipinitialspace=True)
    data = list(r)

# transpose row/col data and convert to list (otherwise, it would be tuple)
col1,col2 = [list(col) for col in zip(*data)]
print(col1)
print(col2)

[397.451, 397.585, 397.719, 397.853, 397.987, 398.121, 398.256, 398.39, 398.524, 398.658, 398.792, 398.926, 399.06, 399.194, 399.328, 399.463, 399.597, 399.731, 399.865, 399.999]
[-48.38, -48.38, -48.38, -18.38, -3.38, 6.62, -0.38, -1.38, 7.62, 4.62, -4.38, 12.62, 5.62, -6.38, -6.38, 0.62, -6.38, -12.38, 1.62, 2.62]

Using pandas:

import pandas as pd
data = pd.read_csv('input.csv',sep=' ',skipinitialspace=True,header=None)
col1 = list(data[0])
col2 = list(data[1])
print(col1)
print(col2)

Using no imports:

with open('input.csv') as f:
    data = [[float(n) for n in row.split()] for row in f]
col1,col2 = [list(n) for n in zip(*data)]
print(col1)
print(col2)