将 .txt 或 excel 文件的行读入元组答案

【问题标题】：Read lines of .txt or excel file into tuples将 .txt 或 excel 文件的行读入元组
【发布时间】：2019-11-10 14:55:07
【问题描述】：

我想逐行阅读两个 .txt 文件。这些文件的数据分为五列

文件_1：

843.19598 2396.10278 3579.13778 4210.15674 4209.37549
841.93976 2397.21948 3573.11963 4205.89209 4226.73926
842.01642 2397.72266 3573.06494 4202.88379 4226.93799
842.22083 2397.47974 3574.27515 4204.19043 4223.82088
842.42065 2397.20142 3575.47437 4205.52246 4220.64795

文件_2：

3586.02124 2391.50342 837.45227 -837.29681 -2385.97513
3587.69238 2387.48218 836.60445 -840.75067 -2390.17529
3588.44531 2387.44556 836.00555 -840.79022 -2389.77612
3588.08203 2388.25439 836.26544 -840.17017 -2389.07544
3587.66553 2389.05566 836.53046 -839.53912 -2388.40405

文件的每一行都必须转换成一个元组。例如对于两个文件的第一行，输出应该是：

FILE_1/1stLine = (843.19598, 2396.10278, 3579.13778, 4210.15674, 4209.37549)  

FILE_2/1stline = (3586.02124, 2391.50342, 837.45227, -837.29681, -2385.97513)

然后我需要将这两个文件的行组合成一个新的变量aux，其中第一个元素是FILE_1的一行，第二个元素是FILE_2中相同位置的行

aux = (FILE_1/1stLine, FILE_2/1stline) ----- aux 1stLine
aux = (FILE_1/2ndLine, FILE_2/2ndline) ----- aux 2ndLine
.
.
aux = (FILE_1/LastLine, FILE_2/Lastline) ----- aux 2ndLastLine

例如，取两个文件的第一行，第一个 aux 必须是：

((843.19598, 2396.10278, 3579.13778, 4210.15674, 4209.37549), (3586.02124, 2391.50342, 837.45227, -837.29681, -2385.97513))

有什么想法吗？

f1 = open("FILE_1.txt", "r")
f2 = open("FILE_2.txt", "r")
for a in f1:
    for b in f2:
        x = tuple(a)
        y = tuple(b)
        aux = (x, y)

这段代码的结果是：

('8', '4', '3', '.', '1', '9', '5', '9', '8', ' ', '2', '3', '9', '6', '.', '1', '0', '2', '7', '8', ' ', '3', '5', '7', '9', '.', '1', '3', '7', '7', '8', ' ', '4', '2', '1', '0', '.', '1', '5', '6', '7', '4', ' ', '4', '2', '0', '9', '.', '3', '7', '5', '4', '9', '\n')
('3', '5', '8', '6', '.', '0', '2', '1', '2', '4', ' ', '2', '3', '9', '1', '.', '5', '0', '3', '4', '2', ' ', '8', '3', '7', '.', '4', '5', '2', '2', '7', ' ', '-', '8', '3', '7', '.', '2', '9', '6', '8', '1', ' ', '-', '2', '3', '8', '5', '.', '9', '7', '5', '1', '3', '\n')
(('8', '4', '3', '.', '1', '9', '5', '9', '8', ' ', '2', '3', '9', '6', '.', '1', '0', '2', '7', '8', ' ', '3', '5', '7', '9', '.', '1', '3', '7', '7', '8', ' ', '4', '2', '1', '0', '.', '1', '5', '6', '7', '4', ' ', '4', '2', '0', '9', '.', '3', '7', '5', '4', '9', '\n'), ('3', '5', '8', '6', '.', '0', '2', '1', '2', '4', ' ', '2', '3', '9', '1', '.', '5', '0', '3', '4', '2', ' ', '8', '3', '7', '.', '4', '5', '2', '2', '7', ' ', '-', '8', '3', '7', '.', '2', '9', '6', '8', '1', ' ', '-', '2', '3', '8', '5', '.', '9', '7', '5', '1', '3', '\n'))

非常感谢！

我需要像 843.19598 这样不带引号的元素，而不是像 '843.19598' 这样获取 f1/f2 的每个元素。

让我展示这些数据作为输入的代码（以一组点为例）

问题是我必须从这些文件中读取 x 和 y，并且对于每个集合我需要拟合一个椭圆。

import ellipses as el
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Ellipse



x = (5727.53135,  7147.62235, 10330.93573,  8711.17228, 7630.40262,
        4777.24983,  4828.27655,  9449.94416,  5203.81323,  6299.44811,
        6494.21906)

y = (67157.77567 , 66568.50068 , 55922.56257 , 54887.47348 ,
       65150.14064 , 66529.91705 , 65934.25548 , 55351.57612 ,
       63123.5103  , 67181.141725, 56321.36025)

data = (x, y)

lsqe = el.LSqEllipse()
lsqe.fit(data)
center, width, height, phi = lsqe.parameters()

print (center, width, height, phi)

plt.close('all')
fig = plt.figure(figsize=(6,6))
ax = fig.add_subplot(111)
ax.axis('equal')
ax.plot(data[0], data[1], 'ro', label='test data', zorder=1)

ellipse = Ellipse(xy=center, width=2*width, height=2*height, angle=np.rad2deg(phi),
               edgecolor='b', fc='None', lw=2, label='Fit', zorder = 2)
ax.add_patch(ellipse)

plt.legend()
plt.show()

【问题讨论】：

请将此评论添加到问题中。你可以编辑它。我为你的问题添加了一些标签。
完成了，我添加了将数据拟合到椭圆的代码。
你只需要在绘图之前做 float(x) 。它将字符串转换为浮点数。
抱歉，您在绘图前使用 float (x) 是什么意思？
删除引号并将值用作数字。这将解决“我需要像 843.19598 这样没有引号的元素，而不是像 '843.19598' 那样获取 f1/f2 的每个元素”

标签： python python-3.x pandas tuples

【解决方案1】：

数据集

FILE 1 (saved as f1.csv and f1.xls)
843.19598 2396.10278 3579.13778 4210.15674 4209.37549
841.93976 2397.21948 3573.11963 4205.89209 4226.73926
842.01642 2397.72266 3573.06494 4202.88379 4226.93799
842.22083 2397.47974 3574.27515 4204.19043 4223.82088
842.42065 2397.20142 3575.47437 4205.52246 4220.64795

FILE 2 (saved as f2.csv and f2.xls)
3586.02124 2391.50342 837.45227 -837.29681 -2385.97513
3587.69238 2387.48218 836.60445 -840.75067 -2390.17529
3588.44531 2387.44556 836.00555 -840.79022 -2389.77612
3588.08203 2388.25439 836.26544 -840.17017 -2389.07544
3587.66553 2389.05566 836.53046 -839.53912 -2388.40405

使用导入 csv（适用于 ascii 文件，即 .csv、.txt 等）

import csv

# Files to read
files = ['f1.csv', 'f2.csv']
tup_files = ()
aux = ()

# Read each file and concatenate to tup_files
for file in files:
    with open(file) as csv_file:
        csv_reader = csv.reader(csv_file, delimiter=' ')
        tmp_rows = ()
        for row in csv_reader:
            tmp_rows += (tuple(row), )  

    tup_files += (tmp_rows, )

for row_f1, row_f2 in zip(tup_files[0], tup_files[1]):
    aux += (row_f1, row_f2)

print(f'printing f1\n{tup_files[0]}\n')
print(f'printing f2\n{tup_files[1]}\n')
print(f'printing aux\n{aux}')

使用 pandas（适用于 .xls）

import pandas as pd

# Files to read
files = ['f1.xls', 'f2.xls']
tup_files = ()
aux = ()

# Read each file and concatenate to tup_files
for file in files:
    data = pd.read_excel(file, header=None)
    tup_files += (tuple(data.itertuples(index=False, name=None)), )

for row_f1, row_f2 in zip(tup_files[0], tup_files[1]):
    aux += (row_f1, row_f2)

print(f'printing f1\n{tup_files[0]}\n')
print(f'printing f2\n{tup_files[1]}\n')
print(f'printing aux\n{aux}')

产量：

printing f1
(('843.19598', '2396.10278', '3579.13778', '4210.15674', '4209.37549'), 
 ('841.93976', '2397.21948', '3573.11963', '4205.89209', '4226.73926'),
 ('842.01642', '2397.72266', '3573.06494', '4202.88379', '4226.93799'),
 ('842.22083', '2397.47974', '3574.27515', '4204.19043', '4223.82088'),
 ('842.42065', '2397.20142', '3575.47437', '4205.52246', '4220.64795'))

printing f2
(('3586.02124', '2391.50342', '837.45227', '-837.29681', '-2385.97513'),
 ('3587.69238', '2387.48218', '836.60445', '-840.75067', '-2390.17529'), 
 ('3588.44531', '2387.44556', '836.00555', '-840.79022', '-2389.77612'), 
 ('3588.08203', '2388.25439', '836.26544', '-840.17017', '-2389.07544'), 
 ('3587.66553', '2389.05566', '836.53046', '-839.53912', '-2388.40405'))

printing aux
(('843.19598', '2396.10278', '3579.13778', '4210.15674', '4209.37549'), 
 ('3586.02124', '2391.50342', '837.45227', '-837.29681', '-2385.97513'), 
 ('841.93976', '2397.21948', '3573.11963', '4205.89209', '4226.73926'), 
 ('3587.69238', '2387.48218', '836.60445', '-840.75067', '-2390.17529'), 
 ('842.01642', '2397.72266', '3573.06494', '4202.88379', '4226.93799'), 
 ('3588.44531', '2387.44556', '836.00555', '-840.79022', '-2389.77612'), 
 ('842.22083', '2397.47974', '3574.27515', '4204.19043', '4223.82088'), 
 ('3588.08203', '2388.25439', '836.26544', '-840.17017', '-2389.07544'), 
 ('842.42065', '2397.20142', '3575.47437', '4205.52246', '4220.64795'), 
 ('3587.66553', '2389.05566', '836.53046', '-839.53912', '-2388.40405'))

根据需要使用元组的结果。

【讨论】：