Performing an index operation in Python-CodePudding

I want to perform an index operation using the list I5 to create a new list I6. However, there seems to be an error in notation.

This is the logic

I6=[[(I5[0][0]),(I5[0][1]-I5[0][0])],[(I5[1][0]),(I5[1][1]-I5[1][0])],...]

The code is

I5 = [[(0.5, -0.5), (1.5, -0.5)], [(0.5, -0.5), (0.5, -1.5)], [(1.5, -0.5), (1.5, -1.5)], [(0.5, -1.5), (1.5, -1.5)]]

for i in range (0,len(I5)):
    I6=I5[i][0]-I5[i][1]
    print(I6)

The error is

in <module>
    I6=I5[i][0]-I5[i][1]

TypeError: unsupported operand type(s) for -: 'tuple' and 'tuple'

The expected output is

I6 = [[(0.5, -0.5), (1, 0)], [(0.5, -0.5), (0, -1)], [(1.5, -0.5), (0, -1)], [(0.5, -1.5), (1, 0)]]

CodePudding user response：

Try:

I5 = [
    [(0.5, -0.5), (1.5, -0.5)],
    [(0.5, -0.5), (0.5, -1.5)],
    [(1.5, -0.5), (1.5, -1.5)],
    [(0.5, -1.5), (1.5, -1.5)],
]

I6 = []
for i in range(0, len(I5)):
    I6.append(
        [I5[i][0], (I5[i][1][0] - I5[i][0][0], I5[i][1][1] - I5[i][0][1])]
    )

print(I6)

Prints:

[
    [(0.5, -0.5), (1.0, 0.0)],
    [(0.5, -0.5), (0.0, -1.0)],
    [(1.5, -0.5), (0.0, -1.0)],
    [(0.5, -1.5), (1.0, 0.0)],
]

CodePudding user response：

I think this code works.


I5 = [[(0.5, -0.5), (1.5, -0.5)], [(0.5, -0.5), (0.5, -1.5)], [(1.5, -0.5), (1.5, -1.5)], [(0.5, -1.5), (1.5, -1.5)]]
I6 = []
for i in range (0,len(I5)):
    I6.append([])
    I6[i].append(I5[i][0])
    toadd = []
    toadd.append(I5[i][1][0]-I5[i][0][0])
    toadd.append(I5[i][1][1]-I5[i][0][1])
    I6[i].append(toadd)
    print(I6)

CodePudding user response：

A concise way is:

I6 = [[s[0], tuple(y - x for x, y in zip(s[0], s[1]))] for s in I5]

which gives:

[[(0.5, -0.5), (1.0, 0.0)], [(0.5, -0.5), (0.0, -1.0)], [(1.5, -0.5), (0.0, -1.0)], [(0.5, -1.5), (1.0, 0.0)]]

Even shorter (but maybe not so transparent):

I6 = [[s[0], tuple(y - x for x, y in zip(*s))] for s in I5]

CodePudding user response：

This seems to give the desired output although the zero values are float rather than int as implied in the question.

I5 = [[(0.5, -0.5), (1.5, -0.5)], [(0.5, -0.5), (0.5, -1.5)], [(1.5, -0.5), (1.5, -1.5)], [(0.5, -1.5), (1.5, -1.5)]]
I6 = []

for e1, e2 in I5:
    I6.append([e1, (e2[0]-e1[0], e2[1]-e1[1])])

print(I6)

Output:

[[(0.5, -0.5), (1.0, 0.0)], [(0.5, -0.5), (0.0, -1.0)], [(1.5, -0.5), (0.0, -1.0)], [(0.5, -1.5), (1.0, 0.0)]]

CodePudding user response：

You can use pandas:

I5 = [[(0.5, -0.5), (1.5, -0.5)], [(0.5, -0.5), (0.5, -1.5)], [(1.5, -0.5), (1.5, -1.5)], [(0.5, -1.5), (1.5, -1.5)]]

import pandas as pd
df = pd.DataFrame(I5)

df[2] = df[0].map(lambda x: x[0])
df[3] = df[0].map(lambda x: x[1])
df[4] = df[1].map(lambda x: x[0])
df[5] = df[1].map(lambda x: x[1])

will return:

#df:
    0           1             2     3       4     5
0   (0.5, -0.5) (1.5, -0.5)   0.5   -0.5    1.5   -0.5
1   (0.5, -0.5) (0.5, -1.5)   0.5   -0.5    0.5   -1.5
2   (1.5, -0.5) (1.5, -1.5)   1.5   -0.5    1.5   -1.5
3   (0.5, -1.5) (1.5, -1.5)   0.5   -1.5    1.5   -1.5

then you can create the new columns you want based on other columns, I think easier than using nested lists:

df[6] = df[3] - df[2]

    0           1           2   3       4   5       6
0   (0.5, -0.5) (1.5, -0.5) 0.5 -0.5    1.5 -0.5    -1.0
1   (0.5, -0.5) (0.5, -1.5) 0.5 -0.5    0.5 -1.5    -1.0
2   (1.5, -0.5) (1.5, -1.5) 1.5 -0.5    1.5 -1.5    -2.0
3   (0.5, -1.5) (1.5, -1.5) 0.5 -1.5    1.5 -1.5    -2.0