读取 csv 文件的 header 并查看它是否与字典键匹配,然后将该键的值写入行

Reading header of csv file and seeing if it matches a dictionary key, then write value of that key to row

基本上我会有一堆小词典,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,其中包含一大堆在 header 中包含单词的列,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,我确实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 headers(首先跳到第 5 列 headers),每次查看是否可以在中找到 header 名称字典,如果是,则将值添加到该行,如果不是,则添加 "no"。这将逐行完成,其中每一行对应一个小词典。此文件使用上述字典的结果为:

到目前为止,我已经能够尝试以下方法,但实际上不起作用:

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")

‘Pandas’或许能帮到你。

这是网站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() 方法根据需要添加一些数据。

希望这些对您有所帮助。

您的问题似乎是要求确保您的 dictionary_list 中的字段存在于记录中。如果该字段原先存在于记录中则将该字段值设置为yes,否则将该字段添加到记录中并设置该字段值为no。

#!/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)

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