读取 csv 文件的标题并查看它是否与字典键匹配，然后将该键的值写入行

Question

基本上我会有一堆小字典，像这样：

dictionary_list = [
{"eight": "yes", "queen": "yes", "we": "yes", "eighteen": "yes"},
{"nine": "yes", "king": "yes","we": "yes", "nineteen": "yes"}
]

然后我有一个 csv 文件，其中包含一大堆列，标题中也包含单词，如下所示： 可能有 500 列，每列有 1 个单词，我不知道列出现的顺序。但是，我知道我的小词典中的任何单词都应该与列中的单词匹配。

我想遍历文件的标题（首先跳过 5 个列标题），每次查看是否可以在字典中找到标题名称，如果可以，则将值添加到该行中，如果没有，加一个“否”。这将逐行完成，其中每一行用于一个小字典。对该文件使用上述字典的结果将是：

到目前为止，我已经能够尝试以下不起作用的方法：

f = open("file.csv", "r")
writer = csv.DictWriter(f)
for dict in dictionary_list: # this is the collection of little dictionaries
    # do some other stuff
    for r in writer: 
        #not sure how to skip 10 columns here. next() seems to work on rows 
        for col in r:
            if col in dict.keys():
                 writer.writerow(dict.values())
             else:
                 writer.writerow("no")

Answer 1

给定一个输入文件headers.csv:

row1,row2,row3,row4,row5,bad,good,eight,nine,queen,three,eighteen,nineteen,king,jack,ace,we,them,you,two

以下代码生成您的输出：

import csv

dictionary_list = [{"eight": "yes", "queen": "yes", "we": "yes", "eighteen": "yes"},
                   {"nine": "yes", "king": "yes","we": "yes", "nineteen": "yes"}]

# Read the input header line as a list
with open('headers.csv',newline='') as f:
    reader = csv.reader(f)
    headers = next(reader)

# Generate the fixed values for the first 5 rows.
rowvals = dict(zip(headers[:5],['x'] * 5))

with open('file.csv', 'w', newline='') as f:
    # When writing a row, restval is the default value when it isn't in the dict row.
    # extrasaction='ignore' prevents complaining if all columns are not present in dict row.
    writer = csv.DictWriter(f,headers,restval='no',extrasaction='ignore')
    writer.writeheader()
    for dictionary in dictionary_list:
        D = dictionary.copy() # needed if the original shouldn't be modified.
        D.update(rowvals)
        writer.writerow(D)

输出：

row1,row2,row3,row4,row5,bad,good,eight,nine,queen,three,eighteen,nineteen,king,jack,ace,we,them,you,two
x,x,x,x,x,no,no,yes,no,yes,no,yes,no,no,no,no,yes,no,no,no
x,x,x,x,x,no,no,no,yes,no,no,no,yes,yes,no,no,yes,no,no,no

Answer 2

“熊猫”可以帮助你。

这里是网站http://pandas.pydata.org/pandas-docs/stable/。

您可以使用pandas.read_csv()方法处理csv文件，并使用Dataframe.append()方法添加一些您想要的数据。

希望这些对您有所帮助。

Answer 3

您的问题似乎是要求确保您的 dictionary_list 中的字段存在记录。如果该字段最初存在于记录中，则将该字段值设置为“是”，否则将该字段添加到该记录中并将该值设置为“否”。

#!/usr/bin/env python3

import csv


dictionary_list = [
    {"eight": "yes", "queen": "yes", "we": "yes", "eighteen": "yes"},
    {"nine": "yes", "king": "yes","them": "yes", "nineteen": "yes"}
]

"""
flatten all the dicionary keys into a uniq list as the
key names will be used for field names and can't be duplicated
"""
field_check = set([k for d in dictionary_list for k in d.keys()])

if __name__ == "__main__":

    with open("file.csv", "r") as f:
        reader = csv.DictReader(f)

        # do not consider the first 10 colums
        field_tail = set(reader.fieldnames[10:])

        """
        initialize yes and no fields as they
        should be the same for every row in the file
        """
        yes_fields = set(field_check & field_tail)
        no_fields = field_check.difference(yes_fields)
        yes_dict = {k:"yes" for k in yes_fields}
        no_dict = {k:"no" for k in no_fields}
        for row in reader:
            row.update(yes_dict)
            row.update(no_dict)
            print(row)