如何将此词典列表转换为csv文件?

import csv
toCSV = [{'name':'bob','age':25,'weight':200},
         {'name':'jim','age':31,'weight':180}]
keys = toCSV[0].keys()
with open('people.csv', 'w', newline='')  as output_file:
    dict_writer = csv.DictWriter(output_file, keys)
    dict_writer.writeheader()
    dict_writer.writerows(toCSV)

在python中,3件事有点不同,但是更简单,更不容易出错。最好告诉CSV文件应该打开 utf8 编码,因为它使数据对其他人更具可移植性(假设您不使用更严格的编码,如 latin1 )

import csv
toCSV = [{'name':'bob','age':25,'weight':200},
         {'name':'jim','age':31,'weight':180}]
with open('people.csv', 'w', encoding='utf8', newline='') as output_file:
    fc = csv.DictWriter(output_file, 
                        fieldnames=toCSV[0].keys(),

                       )
    fc.writeheader()
    fc.writerows(toCSV)

• 请注意 csv 在python3中需要 newline='' 参数,否则在excel/opencalc中打开时,CSV中会出现空行。

pandas 模块。我发现它更能容忍编码问题,而且 在加载文件时,pandas会自动将csv中的字符串数字转换为正确的类型(int、float等)。

import pandas
dataframe = pandas.read_csv(filepath)
list_of_dictionaries = dataframe.to_dict('records')
dataframe.to_csv(filepath)

注:

• 如果您给文件指定了路径,pandas将负责为您打开该文件,并且默认为 在python3中,并找出标题。
• dataframe.to_dict('records')
• pandas还可以更轻松地控制csv文件中列的顺序。默认情况下,它们是按字母顺序排列的,但您可以指定列顺序。加香草 csv文件 模块,你需要给它一个 OrderedDict 或者它们将以随机顺序出现(如果使用python<3.5). 请参见: Preserving column order in Python Pandas DataFrame 更多。

import csv
with open('names.csv', 'w') as csvfile:
    fieldnames = ['first_name', 'last_name']
    writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
    writer.writeheader()
    writer.writerow({'first_name': 'Baked', 'last_name': 'Beans'})

因为@User和@BiXiC请求帮助使用UTF-8,这里是@Matthew解决方案的一个变体(我不能评论,所以我回答。)

import unicodecsv as csv
toCSV = [{'name':'bob','age':25,'weight':200},
         {'name':'jim','age':31,'weight':180}]
keys = toCSV[0].keys()
with open('people.csv', 'wb') as output_file:
    dict_writer = csv.DictWriter(output_file, keys)
    dict_writer.writeheader()
    dict_writer.writerows(toCSV)

write_csv 函数是泛型的):

def gen_rows():
    yield OrderedDict(name='bob', age=25, weight=200)
    yield OrderedDict(name='jim', age=31, weight=180)

def write_csv():
    it = genrows()
    first_row = it.next()  # __next__ in py3
    with open("people.csv", "w") as outfile:
        wr = csv.DictWriter(outfile, fieldnames=list(first_row))
        wr.writeheader()
        wr.writerow(first_row)
        wr.writerows(it)

:此处使用的orderedict构造函数仅保留python中的顺序>3.4. 如果顺序很重要,请使用 OrderedDict([('name', 'bob'),('age',25)]) 形式。

import csv

with open('file_name.csv', 'w') as csv_file:
    writer = csv.writer(csv_file)
    writer.writerow(('colum1', 'colum2', 'colum3'))
    for key, value in dictionary.items():
        writer.writerow([key, value[0], value[1]])

这是将数据写入的最简单方法 .csv文件

import csv
toCSV = [{'name':'bob','age':25,'weight':200},
         {'name':'jim','age':31,'weight':180}]
header=['name','age','weight']     
try:
   with open('output'+str(date.today())+'.csv',mode='w',encoding='utf8',newline='') as output_to_csv:
       dict_csv_writer = csv.DictWriter(output_to_csv, fieldnames=header,dialect='excel')
       dict_csv_writer.writeheader()
       dict_csv_writer.writerows(toCSV)
   print('\nData exported to csv succesfully and sample data')
except IOError as io:
    print('\n',io)