如何将此词典列表转换为 csv 文件?

发布于 2024-09-06 03:48:59 字数 234 浏览 11 评论 0原文

我有一个看起来像这样的字典列表:

toCSV = [{'name':'bob','age':25,'weight':200},{'name':'jim','age':31,'weight':180}]

我应该怎么做才能将其转换为看起来像这样的 csv 文件:

name,age,weight
bob,25,200
jim,31,180

I have a list of dictionaries that looks something like this:

toCSV = [{'name':'bob','age':25,'weight':200},{'name':'jim','age':31,'weight':180}]

What should I do to convert this to a csv file that looks something like this:

name,age,weight
bob,25,200
jim,31,180

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评论(8

宣告ˉ结束 2024-09-13 03:48:59
import csv

to_csv = [
    {'name': 'bob', 'age': 25, 'weight': 200},
    {'name': 'jim', 'age': 31, 'weight': 180},
]

keys = to_csv[0].keys()

with open('people.csv', 'w', newline='') as output_file:
    dict_writer = csv.DictWriter(output_file, keys)
    dict_writer.writeheader()
    dict_writer.writerows(to_csv)
import csv

to_csv = [
    {'name': 'bob', 'age': 25, 'weight': 200},
    {'name': 'jim', 'age': 31, 'weight': 180},
]

keys = to_csv[0].keys()

with open('people.csv', 'w', newline='') as output_file:
    dict_writer = csv.DictWriter(output_file, keys)
    dict_writer.writeheader()
    dict_writer.writerows(to_csv)
遮云壑 2024-09-13 03:48:59

在 python 3 中,情况略有不同,但更简单且不易出错。最好告诉 CSV 您的文件应该使用 utf8 编码打开,因为它使该数据更容易移植到其他人(假设您没有使用限制性更强的编码,例如 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,python 3 中的 csv 需要 newline='' 参数,否则在 excel/opencalc 中打开时,CSV 中会出现空行。

或者:我更喜欢使用 pandas 模块中的 csv 处理程序。我发现它对编码问题的容忍度更高,并且 pandas 在加载文件时会自动将 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)

注意:

  • pandas 将负责打开如果你给它一个路径,它就会为你提供文件,并且在 python3 中默认为 utf8,并找出标头。
  • 数据框与 CSV 提供的结构不同,因此您在加载时添加一行以获得相同的内容:dataframe.to_dict('records')
  • pandas 还使控制数据框变得更加容易csv 文件中的列顺序。默认情况下,它们按字母顺序排列,但您可以指定列顺序。使用普通 csv 模块,您需要为其提供一个 OrderedDict ,否则它们将以随机顺序出现(如果在 python <3.5 中工作)。有关更多信息,请参阅:在 Python Pandas DataFrame 中保留列顺序

In python 3 things are a little different, but way simpler and less error prone. It's a good idea to tell the CSV your file should be opened with utf8 encoding, as it makes that data more portable to others (assuming you aren't using a more restrictive encoding, like 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)
  • Note that csv in python 3 needs the newline='' parameter, otherwise you get blank lines in your CSV when opening in excel/opencalc.

Alternatively: I prefer use to the csv handler in the pandas module. I find it is more tolerant of encoding issues, and pandas will automatically convert string numbers in CSVs into the correct type (int,float,etc) when loading the file.

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

Note:

  • pandas will take care of opening the file for you if you give it a path, and will default to utf8 in python3, and figure out headers too.
  • a dataframe is not the same structure as what CSV gives you, so you add one line upon loading to get the same thing: dataframe.to_dict('records')
  • pandas also makes it much easier to control the order of columns in your csv file. By default, they're alphabetical, but you can specify the column order. With vanilla csv module, you need to feed it an OrderedDict or they'll appear in a random order (if working in python < 3.5). See: Preserving column order in Python Pandas DataFrame for more.
渔村楼浪 2024-09-13 03:48:59

这是当你有一个字典列表时:

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'})

this is when you have one dictionary list:

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'})
不奢求什么 2024-09-13 03:48:59

Pandas 的简短解决方案

import pandas as pd

list_of_dicts = [
    {'name': 'bob', 'age': 25, 'weight': 200},
    {'name': 'jim', 'age': 31, 'weight': 180},
]

df = pd.DataFrame(list_of_dicts) 
df.to_csv("names.csv", index=False)

a short solution with Pandas

import pandas as pd

list_of_dicts = [
    {'name': 'bob', 'age': 25, 'weight': 200},
    {'name': 'jim', 'age': 31, 'weight': 180},
]

df = pd.DataFrame(list_of_dicts) 
df.to_csv("names.csv", index=False)
泅渡 2024-09-13 03:48:59

因为@User 和@BiXiC 在此寻求有关UTF-8 的帮助,这是@Matthew 的解决方案的变体。 (我没有权限发表评论,所以我来回答一下。)

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)

Because @User and @BiXiC asked for help with UTF-8 here a variation of the solution by @Matthew. (I'm not allowed to comment, so I'm answering.)

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)
别再吹冷风 2024-09-13 03:48:59

这是另一个更通用的解决方案,假设您没有行列表(可能它们不适合内存)或标题副本(可能 write_csv 函数是通用的):

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)

< em>注意:这里使用的 OrderedDict 构造函数仅保留 python >3.4 中的顺序。如果顺序很重要,请使用 OrderedDict([('name', 'bob'),('age',25)]) 表单。

Here is another, more general solution assuming you don't have a list of rows (maybe they don't fit in memory) or a copy of the headers (maybe the write_csv function is generic):

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)

Note: the OrderedDict constructor used here only preserves order in python >3.4. If order is important, use the OrderedDict([('name', 'bob'),('age',25)]) form.

旧城烟雨 2024-09-13 03:48:59
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 .csv 文件的最简单方法

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]])

This would be the simplest way to write data to .csv file

离旧人 2024-09-13 03:48:59
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)
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)
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