將嵌套的CSV數據轉換為json

Question

我有一個 csv，格式如下：

p1,p2,p3,p4,p5,p6,p7,p8,p9
u1,u2,u3,u4,u5,u6,u7,u8,u9
10,500,10,10,6.192187,0,0,10.3313,8.58659
2,150,5,3,6.7125,8.497266,9.130859,6.46657,7.645142111
,,,4,6.960938,9.472656,,6.64784,8.060439698
,,,5,7.819531,0,0,6.88975,8.972818303

其中“p”代表屬性，“u”代表單位。 請注意，如果該列的后續值相同，則存在缺失值。 不幸的是我不能填充它們。

我的目標是使用 python 將 csv 轉換為 JSON。格式應類似於以下結構：

val1:{
      val2:{
        val3:{ [val4,val5,val6,val7,val8,val9]
                    }}}

val1:{
      val2:{
        val3:{ [val4,val5,val6,val7,val8,val9],
               [val4,val5,val6,val7,val8,val9],
               [val4,val5,val6,val7,val8,val9],
                 }}}

請注意，前兩行可以忽略。 我有以下 python 代碼開始：

import csv
import json
 
 
# Function to convert a CSV to JSON
# Takes the file paths as arguments


def make_json(csvFilePath, jsonFilePath):
 
    # create a dictionary
    data = {}
 
    # Open a csv reader called DictReader
    with open(csvFilePath,  mode='r', encoding='utf-8-sig') as csvf:
        csvReader = csv.DictReader(csvf,delimiter =',')

    for rows in csvReader:
        # Assuming a column named 'p1' to
        # be the primary key
        key = rows['p1']
        data[key] = rows
    
# Open a json writer, and use the json.dumps()
# function to dump data
with open(jsonFilePath, 'w', encoding='utf-8') as jsonf:
    jsonf.write(json.dumps(data, indent=4))
     
# Driver Code
 
# Decide the two file paths according to your
# computer system
csvFilePath = r'./data/chart-0.csv'
jsonFilePath = r'./js/try.js'

 
# Call the make_json function
make_json(csvFilePath, jsonFilePath)

我應該怎么go一下這個？

Answer 1

如果要將.csv轉換為.json，請使用pandas和json

首先，我們將 csv 轉換為字典，然后將 dict 轉換為 json

import pandas as pd
import json

file = pd.read_csv('file.csv')
print(json.dumps(file.to_dict(), indent=4))

Output：

{
    "p1": {
        "0": "u1",
        "1": "10",
        "2": "2",
        "3": NaN,
        "4": NaN
    },
    "p2": {
        "0": "u2",
        "1": "500",
        "2": "150",
        "3": NaN,
        "4": NaN
    },
    "p3": {
        "0": "u3",
        "1": "10",
        "2": "5",
        "3": NaN,
        "4": NaN
    },
    "p4": {
        "0": "u4",
        "1": "10",
        "2": "3",
        "3": "4",
        "4": "5"
    },
    "p5": {
        "0": "u5",
        "1": "6.192187",
        "2": "6.7125",
        "3": "6.960938",
        "4": "7.819531"
    },
    "p6": {
        "0": "u6",
        "1": "0",
        "2": "8.497266",
        "3": "9.472656",
        "4": "0"
    },
    "p7": {
        "0": "u7",
        "1": "0",
        "2": "9.130859",
        "3": NaN,
        "4": "0"
    },
    "p8": {
        "0": "u8",
        "1": "10.3313",
        "2": "6.46657",
        "3": "6.64784",
        "4": "6.88975"
    },
    "p9": {
        "0": "u9",
        "1": "8.58659",
        "2": "7.645142111",
        "3": "8.060439698",
        "4": "8.972818303"
    }
}

Answer 2

如果我了解您的問題中顯示的所需 output 格式在處理缺失值方面的含義，我認為這會滿足您的要求。

import csv
import json


# Function to convert a CSV to JSON
# Takes the file paths as arguments
def make_json(csvFilePath, jsonFilePath):

    # create a dictionary
    data = {}

    # Open and read with a csv reader.
    with open(csvFilePath,  mode='r', encoding='utf-8-sig') as csvf:
        csvReader = csv.reader(csvf, delimiter =',')
        next(csvReader); next(csvReader)  # Skip first 2 rows.
        prev_key = None
        for row in csvReader:
            key = row[0:3]
            if not all(key):  # If keys missing, use previous key.
                data[prev_key[0]][prev_key[1]][prev_key[2]].append(row[4:])
            else:
                data.setdefault(key[0], {}).setdefault(key[1], {}).setdefault(key[2], [])
                data[key[0]][key[1]][key[2]].append(row[4:])
                prev_key = key

    # Open a json writer, and use the json.dumps()
    # function to dump data
    with open(jsonFilePath, 'w', encoding='utf-8') as jsonf:
        jsonf.write(json.dumps(data, indent=4))


# Driver Code

# Decide the two file paths according to your
# computer system
csvFilePath = 'chart-0.csv'
jsonFilePath = 'try.json'


# Call the make_json function
make_json(csvFilePath, jsonFilePath)

運行后JSON output文件內容：

{
    "10": {
        "500": {
            "10": [
                [
                    "6.192187",
                    "0",
                    "0",
                    "10.3313",
                    "8.58659"
                ]
            ]
        }
    },
    "2": {
        "150": {
            "5": [
                [
                    "6.7125",
                    "8.497266",
                    "9.130859",
                    "6.46657",
                    "7.645142111"
                ],
                [
                    "6.960938",
                    "9.472656",
                    "",
                    "6.64784",
                    "8.060439698"
                ],
                [
                    "7.819531",
                    "0",
                    "0",
                    "6.88975",
                    "8.972818303"
                ]
            ]
        }
    }
}