如何添加标头以读取 Python CSV 文件的输出？

Question

我有一个 csv 文件，看起来像这样：

我有以下代码，它读取 csv 文件，然后可以打印/访问 CSV 文件中的信息。

import csv

class CsvReader:
    
    with open("Items.csv") as fp:
        reader = csv.reader(fp, delimiter=",", quotechar='"')
        next(reader, None)  # skip the headers
        data_read = [row for row in reader]

    print(data_read[0])

我将其作为打印的输出

['1', '5.99$, '1', 'Blueberry Muffin']

我如何将其格式化为字典，以标题作为键，信息作为元素？

例如，代码将输出：

{Item #: 1, Price: 5.99, Quantity: 1, Name: Blueberry Muffin}

我在这篇文章中引用并看到了很多相似之处：How do I read and write CSV files with Python?

但无法找到有关如何以这种方式专门格式化输出的更多细节，而不使用诸如 pandas 之类的东西，我不打算使用它。

Answer 1

如果您希望字典键作为字段（即列）那么您为什么要跳过它们。 这是简单的解决方案。

import csv

class CsvReader:
    with open("Item.csv") as fp:
        reader = csv.reader(fp, delimiter=",", quotechar='"')
        fields = next(reader)
        data_read = []
        for row in reader:
            data_read.append(dict(zip(fields, row)))

    print(data_read[0])

首先存储列名称并将其与每个行元素映射。

Answer 2

有几种方法可以做到这一点......我同意使用 Pandas 来读取简单文件可能有点大材小用。你可能会说，即使使用

csv_reader

也太过分了。 :)

无论如何，这里有 3 种变化。您需要做的就是捕获标签并将它们用作字典中的键。请注意，下面的方法将为您提供“字典列表”（或熊猫语中的“记录”类型格式）。另一种选择是使用项目编号作为第一个键的“词典的词典”，但本质上它与列表索引相同......所以大致相同。您也可能会放弃捕获项目编号，因为这只是结果列表中的索引，但这是细微差别。

您可能还有兴趣在最后一个变体中显示的

named tuple

中捕获它们。非常容易合作...

# Grocery Reader

import csv
from collections import namedtuple


with open("data.csv") as fp:
    reader = csv.reader(fp, delimiter=",", quotechar='"')
    labels = next(reader, None)  # capture the headers
    result = []
    for row in reader:  # iterate the remaining rows
        pairs = zip(labels, row)
        result.append(dict(pairs))

print(result)

# the above isn't real satisfying as the numeric objects are captured as strings.
# so...
with open("data.csv") as fp:
    reader = csv.reader(fp, delimiter=",", quotechar='"')
    labels = next(reader, None)  # capture the headers
    result = []
    for row in reader:  # iterate the remaining rows
        row[0] = int(row[0])
        row[1] = float(row[1])
        row[2] = int(row[2])
        pairs = zip(labels, row)
        result.append(dict(pairs))

print(result)

with open("data.csv") as fp:
    reader = csv.reader(fp, delimiter=",", quotechar='"')
    labels = next(reader, None)  # capture the headers
    # make lowercase...just for standardization
    labels = [t.lower() for t in labels]
    Grocery = namedtuple('Grocery', labels)
    result = []
    for row in reader:  # iterate the remaining rows
        row[0] = int(row[0])
        row[1] = float(row[1])
        row[2] = int(row[2])
        grocery = Grocery(*row)
        result.append(grocery)

for grocery in result:
    # the below presumes you know the names inside the named tuple...
    print(f'a {grocery.name} costs {grocery.price}')

产量（data.csv可推断）

[{'Item': '1', 'Price': '4.99', 'Qty': '2', 'Name': 'Muffin'}, {'Item': '2', 'Price': '1.25', 'Qty': '6', 'Name': 'Gum'}, {'Item': '3', 'Price': '2.50', 'Qty': '8', 'Name': 'Cookie'}]
[{'Item': 1, 'Price': 4.99, 'Qty': 2, 'Name': 'Muffin'}, {'Item': 2, 'Price': 1.25, 'Qty': 6, 'Name': 'Gum'}, {'Item': 3, 'Price': 2.5, 'Qty': 8, 'Name': 'Cookie'}]
a Muffin costs 4.99
a Gum costs 1.25
a Cookie costs 2.5

Answer 3

使用此处的

DictReader

csv。

cat food.csv                                                                                                                                                                                                           
Item #,Price,Quantity,Name
1, 5.99$,1,Blueberry Muffin


import csv
with open('food.csv') as csv_file:
    reader = csv.DictReader(csv_file,delimiter=",", quotechar='"')
    for row in reader:
        print(dict(row))

{'Item #': '1', 'Price': ' 5.99$', 'Quantity': '1', 'Name': 'Blueberry Muffin'}

Answer 4

1. 打开文件
2. 通过

   csv.reader

读取/解析文件
3. 使用

   next

   作为标题行读取第一行
4. 阅读剩余的行。检查列是整数、浮点数还是字符串。
5. 您现在拥有

   results

   数组，每行都有一个很好的键/值字典，并具有响应的标头名称。

这就是我用的：

with open(args.filename) as csvfile:
    headers = []
    result = []

    reader = csv.reader(csvfile, delimiter=',', quotechar='"')
    # Read headers from first row
    headers = next(reader)
    for row in reader:  # iterate the remaining rows
        parsed_row = {}
        for header, value in zip(headers, row):
            if value.isdigit():  # Check if value is a digit
                parsed_row[header] = int(value)  # Convert to integer if it's a digit
            elif value.replace('.', '', 1).isdigit():  # Check if value is a float
                parsed_row[header] = float(value)  # Convert to float if it's a float
            else:
                parsed_row[header] = value  # Otherwise, keep it as a string
        result.append(parsed_row)