Python - 在 python 中读取 csv 的内容并附加它

Question

 import csv
 with open("somecities.csv") as f:
    reader = csv.DictReader(f)
    data = [r for r in reader]

somecities.csv 的内容：

Country,Capital,CountryPop,AreaSqKm

Canada,Ottawa,35151728,9984670

USA,Washington DC,323127513,9833520

Japan,Tokyo,126740000,377972

Luxembourg,Luxembourg City,576249,2586

python 新手，我正在尝试读取并附加一个 csv 文件。我花了一些时间尝试对类似问题的一些回答，但没有运气——这就是为什么我认为上面的代码毫无用处。

我本质上想要实现的是使用字典将 CSV 中的每一行存储在内存中，国家名称作为键，值是包含表中其他信息的元组，按照它们在CSV 文件。

从那里我尝试将另外三个城市添加到 csv（国家、首都、CountryPop、AreaSqKm）并查看更新的 csv。我应该如何去做这一切？

对更新后的 csv 的期望添加是：

巴西，巴西利亚，211224219, 8358140

中国，北京，1403500365, 9388211

比利时，布鲁塞尔，11250000, 30528

编辑：

Import csv
with open("somecities.csv", "r") as csvinput:
    with open(" somecities_update.csv", "w") as csvresult:
        writer = csv.writer(csvresult, lineterminator='\n')
        reader = csv.reader(csvinput)
        all = []
        headers = next(reader)
        for row in reader:
            all.append(row)

        # Now we write to the new file
        writer.write(headers)
        for record in all:
            writer.write(record)


        #row.append(Brazil, Brasília, 211224219, 8358140)
        #row.append(China, Beijing, 1403500365, 9388211)
        #row.append(Belgium, Brussels, 11250000, 30528)

Answer 1

DictReader 只会将每一行表示为字典，例如：

{
  "Country": "Canada",
  ...,
  "AreaSqKm": "9984670"
}

如果要将整个 CSV 存储为字典，则必须创建自己的：

import csv

all_data = {}

with open("somecities.csv", "r") as f:
    reader = csv.DictReader(f)
    for row in reader:
        # Key = country, values = tuple containing the rest of the data.
        all_data[row["Country"]] = (row["Capital"], row["CountryPop"], row["AreaSqKm"])

# Add the new cities to the dictionary here...

# To write the data to a new CSV
with open("newcities.csv", "w") as f:
    writer = csv.writer(f)
    for key, values in all_data.items():
        writer.writerow([key] + list(values))

不过，正如其他人所说，pandas 库可能是一个不错的选择。查看它的 read_csv 和 to_csv 函数。

Answer 2

因此，假设您可以为此使用 pandas，我会这样做：

import pandas as pd   

df1 = pd.read_csv('your_initial_file.csv', index_col='Country')
df2 = pd.read_csv('your_second_file.csv', index_col='Country')

dfs = [df1,df2]

final_df = pd.concat(dfs)

Answer 3

通过如下的列表构造创建和列出并附加新值的另一个想法，未经测试：

import csv
with open("somecities.csv", "r") as csvinput:
    with open("result.csv", "w") as csvresult:
        writer = csv.writer(csvresult, lineterminator='\n')
        reader = csv.reader(csvinput)
        all = []
        row = next(reader)
        row.append(Brazil, Brasília, 211224219, 8358140)
        row.append(China, Beijing, 1403500365, 9388211)
        all.append(row)
        for row in reader:
            row.append(row[0])
            all.append(row)
        writer.writerows(all)

我看到的最简单的Form，在python 3.6中测试过

使用 'a' 参数打开文件允许您追加到文件末尾，而不是简单地覆盖现有内容。试试看。

>>> with open("somecities.csv", "a") as fd:
...     fd.write("Brazil, Brasília, 211224219, 8358140")

或

#!/usr/bin/python3.6
import csv
fields=['Brazil', 'Brasília', '211224219','8358140']
with open(r'somecities.csv', 'a') as f:
    writer = csv.writer(f)
    writer.writerow(fields)