如何使用熊猫读取和打印CSV中具有常见数据的行

Question

我正在使用以下代码，使用python和pandas从csv读取特定行。 但是当我想打印公共数据，文本行时，我陷入了困境。 我要打印包含订单代码为和00157B的行。 PFA我正在使用的场景和附加代码的屏幕截图。

rows = pd.read_csv('SampData.csv', skiprows=[1,3])
print(rows.head())

Answer 1

可以使用熊猫来做到这一点，但这太过分了。我只建议使用csv模块，该模块非常易于使用，并且包含许多在线文档。我认为这是一个玩具示例，几乎可以满足您的需求

data.csv文件：

Order Number, Item, quantity
76XY, Cheese, 3
88TG, Broccoli, 44
76XY, Cookies, 1000
98UU, Coke, 1

操纵2个csv文件的简短文件：

import csv
input_file = 'data.csv'
output_file = 'found_orders.csv'
magic_order = '76XY'

with open(output_file, 'w') as target:
    target_writer = csv.writer(target)

    # open the source
    with open(input_file, 'r') as source:
        source_reader = csv.reader(source)
        # now both are "open and ready"
        # get the header from the first read of the source
        header = source_reader.__next__()

        # write to the modified file
        target_writer.writerow(header)

        # now use loop to loop through all rows and look for the order number
        # if found, print it to console and write it out to new csv
        # some extra print statements to see what is going on.  Recall
        # when csv reader reads a row, it reads it in as a list
        for row in source_reader:
            print('just read row: ', row)
            order = row[0]  # the position in the list of the order
            if order == magic_order:
                print('it matches the magic order')
                target_writer.writerow(row)
            else:
                print('not a match')
            print()

# if you use the 'with' command structure, it will close the files automatically
print('done')

输出（至控制台）。输出文件就是您期望看到的。：

just read row:  ['76XY', ' Cheese', ' 3']
it matches the magic order

just read row:  ['88TG', ' Broccoli', ' 44']
not a match

just read row:  ['76XY', ' Cookies', ' 1000']
it matches the magic order

just read row:  ['98UU', ' Coke', ' 1']
not a match

done
[Finished in 0.0s]

Answer 2

您可以尝试其中之一-

如果您想在OrderCode列中进行整个术语的比较（例如00157B）：

 filtered = rows[rows['OrderCode'] == '00157B'].reset_index(drop=True)
 filtered.to_csv('output.csv', index=False)

如果要在OrderCode列中进行部分比较（例如OrderCodes与< Test 1 >）：

filtered = rows[rows['OrderCode'].str.contains('< Test 1 >')].reset_index(drop=True)
filtered.to_csv('output.csv', index=False)