python - 在删除某些列的同时将CSV转换为JSON

我从OECD下载了有关收入不平等的数据集作为CSV文件。我只想保留数据：LOCATION，TIME，VALUE。

CSV头部的部分如下所示：

"LOCATION","INDICATOR","SUBJECT","MEASURE","FREQUENCY","TIME","Value","Flag Codes"
"AUS","INCOMEINEQ","GINI","INEQ","A","2014",0.337,
"AUS","INCOMEINEQ","GINI","INEQ","A","2016",0.33,
"AUT","INCOMEINEQ","GINI","INEQ","A","2014",0.274,
"AUT","INCOMEINEQ","GINI","INEQ","A","2015",0.276,
"AUT","INCOMEINEQ","GINI","INEQ","A","2016",0.284,

到目前为止，这是我的转换器代码：

#!/usr/bin/env python

"""Universal CSV to JSON converter with scalability options"""

__author__      = "Tim Verlaan 11669128"

import csv
import json

def convert():
    """Convert CSV file to JSON file"""

    # Open the CSV
    f = open( 'data.csv')

    # Change each fieldname to the appropriate field name.
    reader = csv.DictReader( f, fieldnames = ( "LOCATION","INDICATOR","SUBJECT","MEASURE","FREQUENCY","TIME","Value","Flag Codes" ))

    # skip the header
    next(reader)

    # Parse the CSV into JSON
    out = json.dumps( [ row for row in reader ] )

    # Save the JSON
    f = open( 'data_oecd.json', 'w')
    f.write(out)


if __name__ == "__main__":
    """Separating the function, for scalability purposes"""

    convert()

现在的结果：

[{"LOCATION": "AUS", "INDICATOR": "INCOMEINEQ", "SUBJECT": "GINI", "MEASURE": "INEQ", "FREQUENCY": "A", "TIME": "2014", "Value": "0.337", "Flag Codes": ""}, {"LOCATION": "AUS", "INDICATOR": "INCOMEINEQ", "SUBJECT": "GINI", "MEASURE": "INEQ", "FREQUENCY": "A", "TIME": "2016", "Value": "0.33", "Flag Codes": ""}, {"LOCATION": "AUT", "INDICATOR": "INCOMEINEQ", "SUBJECT": "GINI", "MEASURE": "INEQ", "FREQUENCY": "A", "TIME": "2014", "Value": "0.274", "Flag Codes": ""}, {"LOCATION": "AUT", "INDICATOR": "INCOMEINEQ", "SUBJECT": "GINI", "MEASURE": "INEQ", "FREQUENCY": "A", "TIME": "2015", "Value": "0.276", "Flag Codes": ""}, {"LOCATION": "AUT", "INDICATOR": "INCOMEINEQ", "SUBJECT": "GINI", "MEASURE": "INEQ", "FREQUENCY": "A", "TIME": "2016", "Value": "0.284", "Flag Codes": ""}

想要的结果：

[{"LOCATION": "AUS", "TIME": 2014, "VALUE": 0.337}, {"LOCATION": "AUS", "TIME": 2016, "VALUE": 0.33}

最佳答案

使用熊猫很容易做到这一点：

import pandas as pd
df = pd.read_csv('data.csv')
df[['LOCATION', 'TIME', 'Value']].to_json(orient='records')

orient='records'部分很重要，否则它将按列而不是行进行分组

关于python - 在删除某些列的同时将CSV转换为JSON，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/56003944/