用 csv 读卡器读取数值数据

Question

I am trying to read a csv table with csv reader, I want to rewrite the data into a tuple of tuples, where every subtuple contains the data of one row in the original file. I am doing the following and it is working fine, but you can see how ugly it looks.

table1 = tuple()
with open('data.csv', newline='') as f:
    reader = csv.reader(f)
    for row in reader:
        print(row)
        table1 = table1.__add__(tuple([tuple([float(row[0]), float(row[1])])]))  # giving that I know the data is arranged in two columns
print(table1)

The output looks good:

((0.0, 0.0), (0.0, 0.0), (0.00543154732031037, 4.2724591391866636e-05), (0.0347155846128363, 0.00021518683772895567), (0.1014894975795... etc

I am sure there is a better way to do this. Please note that I can only use the builtin modules, this is why I didn't use Pandas. Thank you for any suggestions.

Answer 1

Why not use a list of tuples - then you could use a list comprehension:

with open('data.csv', newline='') as f:
    reader = csv.reader(f)
    table1 = [(float(row[0]), float(row[1])) for row in reader]

If you really need a tuple instead of a list: tuple() accepts iterables, so you can pass the list comprehension to it:

    table1 = tuple((float(row[0]), float(row[1])) for row in reader)

A list/tuple is suitable where you need repeated access/random access to all contained elements.

---

An alternative would be a generator - suitable for all cases where you process the input in a "one-time-only, forward-only" fashion:

def read_data(filename):
    with open(filename, newline='') as f:
        reader = csv.reader(f)
        for row in reader:
            yield (float(row[0]), float(row[1]))


for item in read_data('data.csv'):
    print(item)

Of course you could create a list from the generator as well:

table1 = [item for item in read_data('data.csv')]

# or

table1 = tuple(item for item in read_data('data.csv'))