Python CSV，添加或更改列数据

我有一个CSV文件。然后我有一些必须应用的规则，然后根据这些规则创建一个新的CSV

所以它可以走两条路：

添加一个新列，该列具有自己的标题和数据

获取现有列并更改该列的数据

这就是我目前所拥有的

def applyRules(directory):
    FILES = []
    for f in listdir(OUTPUT_DIR):
        writer = csv.writer(open("%s%s" % (DZINE_DIR, f), "wb"))
        for rule in Substring.objects.filter(source_file=f):

            from_column = rule.from_column
            to_column = rule.to_column

            reader = csv.DictReader(open("%s%s" % (OUTPUT_DIR, f))) 

            headers = reader.fieldnames

            for row in reader:
                if rule.get_rule_type_display() == "substring":
                    string = rule.string.split(",")
                    # alter value
                    row[to_column] = string[0] + row[from_column] + string[1]
                    if rule.from_column == rule.to_column:
                        print rule.from_column
                    else:
                        print rule.from_column

将规则作为FROM_列和TO_列，如果两者相同，则列保持不变，但必须使用规则更新数据，在这种情况下，只需在当前值之前或之后添加字符串

当TO_列不同时，它只是一个新列，在新列下具有如上所述的更改数据

---

因此，目前我只是更改dict的值，但我不确定如何将其恢复到新的CSV等。

如果您以

DictWriter（）

对象的形式打开输出文件，那么您就可以很容易地写出更改后的词典。您确实需要提前确定额外的字段名：

with open(os.path.join(OUTPUT_DIR, f), 'rb') as rfile:
    reader = csv.DictReader(rfile)
    headers = reader.fieldnames 

    rules = Substring.objects.filter(source_file=f).all()

    # pre-process the rules to determine the headers
    for rule in rules:
        from_column = rule.from_column
        to_column = rule.to_column

        if from_column not in headers:
            # problem; perhaps raise an error?
        if to_column not in headers:
            headers.append(to_column

    with open(os.path.join(DZINE_DIR, f), "wb") as wfile:
        writer = csv.DictWriter(wfile, fieldnames=headers)
        for row in reader:
            for rule in rules:
                from_column = rule.from_column
                to_column = rule.to_column

                if rule.get_rule_type_display() == "substring":
                    string = rule.string.split(",")
                    row[to_column] = string[0] + row[from_column] + string[1]

            writer.writerow(reader)