如何在答案/输入的 .csv 文件中找到最接近的数字？

如何解决如何在答案/输入的 .csv 文件中找到最接近的数字？

我正在尝试找出一种方法，从 CSV 文件中的答案中找到最接近的数字。我真的是python的初学者。我尝试了很多想法来让这里的任何事情都能奏效，但我应该多学习。

顺便说一句，有我的代码和 .cvs 文件： life-expectancy.csv

来自 CSV 文件的示例行：

Entity,Code,Year,Life expectancy (years)
Afghanistan,AFG,1950,27.638
Afghanistan,1951,27.878
Afghanistan,1952,28.361
Afghanistan,1953,28.852
...

这是我的代码：

import csv

i = 0
j = 0
average = 0
sum_age = 0
max_age = -1
max_year = -1
max_country = ""
min_age = 1000
min_year = 1000
min_country = ""
lowest_age = 100
lowest_year = 1000
lowest_country = ""
highest_age = -1
highest_year = -1
highest_country = ""

interest = int(input("Enter the year of interest: ")) 
print()

with open("life-expectancy.csv") as life_expct:
    for line in life_expct:
        i = i + 1
        clean_line = line.strip()
        splitting = clean_line.split(",")
     
        
        if i > 1:
            country = splitting[0]
            year = int(splitting[2])
            age = float(splitting[3])

            if max_age < age:
                max_age = age
                max_year = year                
                max_country = country                                

            if min_age > age:
                min_age = age
                min_year = year                
                min_country = country                                  
               
            if interest == year:
                sum_age += age      
                j = j + 1               
            
                if highest_age < age:
                    highest_age = age
                    highest_year = year
                    highest_country = country  

                if lowest_age > age:
                    lowest_age = age
                    lowest_year = year
                    lowest_country = country                   

average = sum_age / j      

print(f"The overall max life expectancy is: {max_age} from {max_country} in {max_year}")
print(f"The overall min life expectancy is: {min_age} from {min_country} in {min_year}")
print()

print(f"For the year {interest}:")
print(f"The average life expectancy across all countries was {average:.2f}")
print(f"The max life expectancy was in {highest_country} with {highest_age}")
print(f"The min life expectancy was in {lowest_country} with {lowest_age}")
print()

我试着把这样的代码放在最后，但我不知道该怎么做。这是我尝试过的代码：

即。

given_value = 2
a_list = [1,5,8]
absolute_difference_function = lambda list_value : abs(list_value - given_value)

closest_value = min(a_list,key=absolute_difference_function)

代码的工作原理：

Enter the year of interest: 1965

The overall max life expectancy is: 86.751 from Monaco in 2019
The overall min life expectancy is: 17.76 from Iceland in 1882

For the year 1965:
The average life expectancy across all countries was 57.55
The max life expectancy was in Sweden with 73.81
The min life expectancy was in Mali with 29.489

所以，基本上我只想了解如何为最近的国家获得最接近的max/min并查看代码以进行学习和练习。

解决方法

也许您想查看 pandas 库，它是为像您这样的项目而设计的。这只是一个非常粗略的例子，很容易改进。

    import pandas as pd
    df = pd.read_csv("life-expectancy.csv",sep=",")

    interest = int(input("Please enter year of interest:"))
    df_interest = df[df['Year'] == interest]

    interest_min = df_interest[df_interest['Life expectancy (years)'] == df_interest['Life expectancy (years)'].min()]
    interest_ent,interest_code,interest_year,interest_exp = interest_min.squeeze().to_list()

    print(f"The overall min life expectancy is: {interest_exp} from {interest_ent} in {interest_year}")