How to make strings in .txt file into columns?

Question

I'm trying to make 3 columns in my .txt file to make it easier to read. This is the code:

file_out = open("Assignment1_Part1.txt", "w")
file_out.write(str(x) + str(fx(x, a)), + str(fx1(x, a)))
file_out.close()

Where x,fx, and fx1 each contain a ton of different values. I want the first value of x to line up with the first value of fx and fx1, however in the .txt file whats happening is all of the x values are typed out first, followed by all the fx, followed by all fx1, like so:

(x)(x)1(x)2 (fx)(fx)1(fx)2 (fx1)(fx1)1(fx1)2

whereas I want it to look like this:

(x) (fx) (fx1)

(x)1 (fx)1 (fx1)1

(x)2 (fx)2 (fx1)2

And so on. Thanks in advance!

edit: whole code

import numpy as np
import matplotlib.pyplot as plt

# Defining Functions ----



def fx(x, a):
    return np.sin(x**a - x**(1 / a) + a * x)


def gx(x, a):
    return a*(x)**(a-1) - (1/a)*x**((1/a) - 1) + a


def fx1(x, a):
    return gx(x, a) * (np.cos(x**a - x**(1 / a) + a * x))


# NR Method ----


def NR(x, function, deriv):
    return x - function/deriv


# Creating x values and defining a ----
x = np.arange(0.00, 5, 0.01)
a = 0.4 + (0223.0 / 25000.0)


# np.column_stack joins two arrays to make a table
ar1 = np.column_stack((x, fx(x, a)))
print(ar1)

plt.plot(x, fx(x, a))
plt.xlabel('x')
plt.ylabel('f(x)')
#plt.savefig("part1")
plt.savefig('part1')
# ar2 = np.column_stack((ar1,fx1(x,a)))
# print(ar2)

file_out = open("Assignment1_Part1.txt", "w")
file_out.write(str(x)+str(fx(x, a))+str(fx1(x, a)))
file_out.close()

Edit 2: Sorry for not making this clear, but the txt file is huge, like 240 lines, the assignment is the plot of a graph so it contains every x value and y value on the graph. This would make adding a newline after each value impossible

is there a reason why you dont use pandas for this? would be much easier and more efficient, save as csv — Ruli, Oct 29 '20 at 20:38
Suggestion: Write a comma separated file which is easily parsed, read by tools, rather than adding (unnecessary) whitespace to the file. Chances are, you’ll regret the whitespace later, and thank yourself for the commas! This is based on the principal of a flat file format. — S3DEV, Oct 29 '20 at 20:38
also I suggest using `with` statement for opening files. look it up its useful — Matiiss, Oct 29 '20 at 20:39
Couldn't you just add a linebreak character at the end of each line? — Andreas, Oct 29 '20 at 20:42
Possibly related: [Transpose list of lists](https://stackoverflow.com/questions/6473679/transpose-list-of-lists) — wwii, Oct 29 '20 at 20:45
@Matiiss Yep its not a list, and I'll get on that now, thank you! — morgy2190, Oct 29 '20 at 20:52
@morgy2190 I posted an answer go check it out (output may not be the **most** readable) — Matiiss, Oct 29 '20 at 20:57

Ruli · Answer 1 · 2020-10-29T21:02:10.347

Would do it like this, not with file open

import numpy as np

data = np.arange(0.00, 5, 0.01)

a = 0.4 + (0223.0 / 25000.0)
def fx(x, a):
    return np.sin(x**a - x**(1 / a) + a * x)


def gx(x, a):
    return a*(x)**(a-1) - (1/a)*x**((1/a) - 1) + a


def fx1(x, a):
    return gx(x, a) * (np.cos(x**a - x**(1 / a) + a * x))

import pandas as pd 

df = pd.DataFrame(columns=["x","fx","fx1"])
df['x'] = data
df['fx'] = fx(df['x'],a)
df['fx1'] = fx1(df['x'],a)
print(df)

df.to_csv("file_name.csv")

The dataframe will look like this (you can select what the delimiter between data is by sep param in to_csv, default is comma):

        x        fx        fx1
0    0.00  0.000000        inf
1    0.01  0.155553   6.545237
2    0.02  0.208523   4.429984
3    0.03  0.247846   3.529117
4    0.04  0.280304   3.001404
..    ...       ...        ...
495  4.95 -0.895714  10.722176
496  4.96 -0.763377  15.623705
497  4.97 -0.586145  19.655121
498  4.98 -0.374017  22.565874
499  4.99 -0.139202  24.166720

Nice answer, clean. Upvote for CSV and steering well clear of arbitrary whitespace! — S3DEV, Oct 29 '20 at 20:58
actually you should try with the actual code (definitions) because it returns arrays or sth — Matiiss, Oct 29 '20 at 20:59
Edited it with actual OPs functions and data, there is no change in my part of code tho, will work just as fine :) — Ruli, Oct 29 '20 at 21:03

score 0 · Accepted Answer · answered Oct 29 '20 at 20:57

here ya go its in gonna be in .txt file now:

import numpy as np
import matplotlib.pyplot as plt

# Defining Functions ----



def fx(x, a):
    return np.sin(x**a - x**(1 / a) + a * x)


def gx(x, a):
    return a*(x)**(a-1) - (1/a)*x**((1/a) - 1) + a


def fx1(x, a):
    return gx(x, a) * (np.cos(x**a - x**(1 / a) + a * x))


# NR Method ----


def NR(x, function, deriv):
    return x - function/deriv


# Creating x values and defining a ----
x = np.arange(0.00, 5, 0.01)
a = 0.4 + (0223.0 / 25000.0)


# np.column_stack joins two arrays to make a table
ar1 = np.column_stack((x, fx(x, a)))
# print(ar1)

plt.plot(x, fx(x, a))
plt.xlabel('x')
plt.ylabel('f(x)')
#plt.savefig("part1")
plt.savefig('part1')
# ar2 = np.column_stack((ar1,fx1(x,a)))
# print(ar2)
temp = []
c = 0
for i in range(len(fx(x, a))):
    str = f'{x[c]}, {fx(x, a)[c]}, {fx1(x, a)[c]}'
    temp.append(str)
    c += 1
with open("Assignment1_Part1.txt", "w") as file:
    file.write('\n'.join(temp))

score 0 · Answer 3 · answered Oct 29 '20 at 22:10

(fake?) data

import numpy as np
x = np.arange(0.001, .1, 0.01)
a = 0.4 + (0223.0 / 25000.0)

Use zip to transpose the results of the three function calls.

data = zip(x,fx(x,a),fx1(x,a))

Create a list of strings from that data and write to a file

with open(the_file,'w') as f:
    f.writelines(f'{x},{y},{z}\n' for (x,y,z) in data)

How to make strings in .txt file into columns?

3 Answers3