是否有一种简单的内置方式将2D Python列表打印为2D矩阵?
所以这个:
[["A", "B"], ["C", "D"]]
会变成类似
的东西A B
C D
我找到了pprint模块,但它似乎没有做我想要的。
答案 0 :(得分:58)
为了让事情变得有趣,让我们尝试一个更大的矩阵:
matrix = [
["Ah!", "We do have some Camembert", "sir"],
["It's a bit", "runny", "sir"],
["Well,", "as a matter of fact it's", "very runny, sir"],
["I think it's runnier", "than you", "like it, sir"]
]
s = [[str(e) for e in row] for row in matrix]
lens = [max(map(len, col)) for col in zip(*s)]
fmt = '\t'.join('{{:{}}}'.format(x) for x in lens)
table = [fmt.format(*row) for row in s]
print '\n'.join(table)
输出:
Ah! We do have some Camembert sir
It's a bit runny sir
Well, as a matter of fact it's very runny, sir
I think it's runnier than you like it, sir
UPD:对于多行单元格,这样的东西应该有效:
text = [
["Ah!", "We do have\nsome Camembert", "sir"],
["It's a bit", "runny", "sir"],
["Well,", "as a matter\nof fact it's", "very runny,\nsir"],
["I think it's\nrunnier", "than you", "like it,\nsir"]
]
from itertools import chain, izip_longest
matrix = chain.from_iterable(
izip_longest(
*(x.splitlines() for x in y),
fillvalue='')
for y in text)
然后应用上面的代码。
答案 1 :(得分:25)
如果您可以使用Pandas(Python数据分析库),您可以通过将其转换为DataFrame对象来漂亮地打印2D矩阵:
from pandas import *
x = [["A", "B"], ["C", "D"]]
print DataFrame(x)
0 1
0 A B
1 C D
答案 2 :(得分:17)
你总是可以使用numpy
import numpy as np
print(np.matrix(A))
答案 3 :(得分:9)
对于Python 3:
matrix = [["A", "B"], ["C", "D"]]
print('\n'.join(['\t'.join([str(cell) for cell in row]) for row in matrix]))
输出
A B
C D
答案 4 :(得分:1)
比freedom 6933 6.0 0.1 57040 13040 ? S 16:55 0:01 /usr/local/bin/php53.cgi -c .:/home/freedom/:/etc index.php
更轻量级的方法是使用pandas
模块
prettytable
的产率:
from prettytable import PrettyTable
x = [["A", "B"], ["C", "D"]]
p = PrettyTable()
for row in x:
p.add_row(row)
print p.get_string(header=False, border=False)
A B
C D
有很多选项可以用不同的方式格式化输出。
有关详细信息,请参阅https://code.google.com/p/prettytable/
答案 5 :(得分:1)
仅提供print('\n'.join(\['\t'.join(\[str(cell) for cell in row\]) for row in matrix\]))
的简单替代方法即可:
matrix = [["A", "B"], ["C", "D"]]
for row in matrix:
print(*row)
说明
*row
打开row
的封包,例如,print("A", "B")
为row
时将调用["A", "B"]
。
注意
如果每列具有相同的宽度,则两个答案的格式都将很好。要更改定界符,请使用sep
关键字。例如,
for row in matrix:
print(*row, sep=', ')
将打印
A, B
C, D
相反。
没有for循环的单行代码
print(*(' '.join(row) for row in matrix), sep='\n')
' '.join(row) for row in matrix)
为每一行返回一个字符串,例如A B
为row
时的["A", "B"]
。
*(' '.join(row) for row in matrix), sep='\n')
解压缩生成器并返回序列'A B', 'C D'
,以便为给出的示例print('A B', 'C D', sep='\n')
调用matrix
。
答案 6 :(得分:0)
您可以更新print
的{{1}},以便在内部循环中打印空间而不是'\ n',而在外部循环中可以使用end=' '
。
print()
我从here https://snakify.org/en/lessons/two_dimensional_lists_arrays/找到了这个解决方案。
答案 7 :(得分:0)
如果您使用的是Notebook / IPython环境,那么sympy可以使用IPython.display打印令人愉悦的矩阵:
import numpy as np
from sympy import Matrix, init_printing
init_printing()
print(np.random.random((3,3)))
display(np.random.random((3,3)))
display(Matrix(np.random.random((3,3))))
答案 8 :(得分:0)
我还建议使用tabulate,它也可以选择打印标题:
def place_image(image: Image, point_xy: tuple[int, int], dest: np.ndarray, alpha: float = 1.) -> np.ndarray:
# Place the merging dot on (500, 500).
offset_x, offset_y = 500 - point_xy[0], 500 - point_xy[1]
# Calculate the location of the image and perform alpha blending.
destination = dest[offset_y:offset_y + image.height, offset_x:offset_x + image.width]
destination = np.uint8(destination * (1 - alpha) + np.array(image) * alpha)
# Copy the 'merged' imaged to the destination location.
dest[offset_y:offset_y + image.height, offset_x:offset_x + image.width] = destination
return dest
# Add the background image blue with alpha 1
new_image = place_image(blue, point_blue, dest=new_image, alpha=1)
# Add the second image with 40% opacity
new_image = place_image(green, point_green, dest=new_image, alpha=0.4)
# Store the resulting image.
image = Image.fromarray(new_image)
image.save('result.png')
:
from tabulate import tabulate
lst = [['London', 20],['Paris', 30]]
print(tabulate(lst, headers=['City', 'Temperature']))
答案 9 :(得分:-1)
请参阅以下代码。
# Define an empty list (intended to be used as a matrix)
matrix = []
matrix.append([1, 2, 3, 4])
matrix.append([4, 6, 7, 8])
print matrix
# Now just print out the two rows separately
print matrix[0]
print matrix[1]