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Question

我编写了一些代码，它接受输入 csv 并使用 pandas 将其转换为 JSON。我需要一些格式化方面的帮助。

输入

Serial UID,Sample ID,For Serial Name,Rev Serial Name
14,10882401,0014F,0014R
18,10881462,0018F,0018R

电流输出

{
    "Serial": "0018F - 0018R",
    "Barcode UID": "18",
    "Sample ID": "10881462"
}

需要的输出

{
    "Serials": {
        "0018F - 0018R" : {
            "Barcode UID": "18",
            "Sample ID": "10881462"
            }
        {
        "0014F - 0014R" :{
            "Barcode UID": "14",
            "Sample ID": "10882401",
        }
    }
}

import pandas as pd
import csv
import json
from itertools import groupby 
from collections import OrderedDict

df = pd.read_csv(f'{my_name}.csv', dtype={
            "Barcode UID" : str,
            "Sample ID" : str,
            "For Serial Name" : str,
            "Rev Serial Name" : str
        })

results = []
temp_serials  = []
count = 0


for (barcode_uid, sample_id), bag in df.groupby(["Barcode UID", "Sample ID"]):
    contents_df = bag.drop(["Barcode UID", "Sample ID"], axis=1)
    subset = [OrderedDict(row) for i,row in contents_df.iterrows()]

    for i in subset:
        (key, val) = i.items()
        temp_barcodes.append("{} - {}".format(key[1],val[1]))

    results.append(OrderedDict([
        ("Barcodes", temp_barcodes[count]),
        ("Barcode UID", barcode_uid),
        ("Sample ID", sample_id)
        ]))
    count+=1



print(json.dumps(results, indent=4))

显示的实际/预期输出。只需要更好地格式化我的 json，对如何使用orderedDict 执行此操作感到困惑。

Answer 1

您是否尝试过使用dict.values()？这是一个例子：

d = {1:10, 2:20, 3:30}
for value in d.values():
    print(value)
# 10
# 20
# 30