如何使用第一行作为键从文本文件制作字典

Question

我正在尝试从文本文件到字典进行 COVID 监控，以检查每个国家/地区的病例。我想制作一个这种格式的字典。

covid ={country{confirmed:value, active:value, recovered:value, suspect:value, probable:value, 
deceased:value}

基于此文本文件。

 COUNTRY, CONFIRMED, ACTIVE, RECOVERED, SUSPECT, PROBABLE, DECEASED
 COUNTRY-A,3,4,2,1,0,0
 COUNTRY-B,1,2,0,2,0,0
 COUNTRY-C,4,2,0,0,3,0
 COUNTRY-D,1,1,1,3,0,0
 COUNTRY-E,3,2,0,2,0,0
 COUNTRY-F,2,0,1,2,0,0
 COUNTRY-G,0,0,1,4,0,0

我试过这段代码，但它打印出国家、已确认、活跃、恢复、可疑、可能、已死亡每次我计算每个国家/地区的病例总数时，它都会给我一个错误。

我试过这段代码：

def covid_monitoring():
country = []
cov_dict = {}
no_cases = []
with open("covidmonitor.txt", 'r') as f:

    for cov in f:
        cov = cov.strip()
        next(f)  # skip header
        if len(cov) >= 1:
            cov_line = cov.split(",")
            country.append(cov_line[0].strip())
            confirmed_file = cov_line[0].strip()
            active_file = cov_line[1].strip()
            recovered_file = cov_line[2].rstrip()
            suspected_file = cov_line[3].strip()
            probable_file = cov_line[4].strip()
            probable_file = cov_line[5].strip()
            deceased_file = cov_line[6].strip(';')
            if confirmed_file not in cov_dict:
                cov_dict[confirmed_file] = [(active_file,  recovered_file, suspected_file, probable_file, probable_file, deceased_file)]
            else:
                cov_dict[confirmed_file].append((active_file, recovered_file, suspected_file, probable_file, probable_file, deceased_file))
   # print(cov_dict)
for cntry in country:
    if cntry in cov_dict:
        for confirm, active, recovered, suspect, probable, deceased in cov_dict[cntry]:
            print("\tCOUNTRY:{cntry}")
            print("\tCONFIRMED:{confirm} ")
            print("\tACTIVE:{active} ")
            print("\tRECOVERED:{recovered} ")
            print("\tSUSPECTED:{suspect} ")
            print("\tPROPBABLE:{probable} ")
            print("\tDECEASED:{deceased} ")
            total_count = int(confirm) + int(active) + int(recovered) + int(suspect) + int(probable) + int(deceased)
            
            no_cases.apped(total_count)
            print(sum(no_cases)

这是我的错误：

     total_count = int(confirm) + int(active) + int(recovered) + int(suspect) + int(probable) + int(deceased)
     ValueError: invalid literal for int() with base 10: 'CONFIRMED'

Answer 1

从代码看，no_cases是一个字符串列表，因为confirm、active、recovered、suspect、probable, deceased 都是字符串并且

total_count= (confirm + active + recovered + suspect + probable + deceased)

也是一个字符串，是拼接而不是求和。

在代码的最后一行对字符串列表调用 sum() 应该会产生如下错误：

TypeError: unsupported operand type(s) for +: 'int' and 'str'

如果要将它们视为数字，则应将所有这些转换为整数。

您的代码也存在其他问题。例如，您调用 next(f) 来跳过 header，但实际上您是在 for 循环内执行文件中的行，因此它可能每隔一行就跳过一次。

Answer 2

如果您想跳过 header，请不要在每个循环中调用 next。

with open("covidmonitor.txt", 'r') as f:
    # f.readlines()[1:] read all line except first line
    for cov in f.readlines()[1:]:
        cov = cov.strip()

好像是csv文件。您也可以像这样在 python 中使用 csv 包。

import csv

no_cases= []
country= []
cov_dict = {}
with open("covidmonitor.txt", 'r') as f:
    cov = csv.DictReader(f, delimiter=",", skipinitialspace=True)
    for country_data in cov:
        total_count = [float(data) for key, data in c.items() if key != 'COUNTRY']
        no_cases.append(sum(total_count))
        country.append(country_data['COUNTRY'])
        cov_dict[country_data['COUNTRY']] = total_count

Answer 3

您可以为此使用 Python pandas 包：

import pandas as pd
data = pd.read_csv("COVID19.TXT", sep=",")
covid = data.set_index("COUNTRY").T.to_dict()
print(covid)

此外，对于分析，您可以轻松地在 pandas 数据框上计算各种函数，然后在需要时转换为字典。在此处查看此 link 以获取更多详细信息：Pandas tutorial

如果您需要更多帮助，请在评论中告诉我。

如何使用第一行作为键从文本文件制作字典

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