PYTHON convert multidimensionale list to JSON data

I'm struggling to bring my array to the right format for the JSON file! Might be an easy question for people with knowledge. I grep the data from different CSV files in the format:

[['Dec', '196610'], ['Oct', '196699'], ['Sep', '131073'], ['Jul', '122050']]

I need to bring it in the format:

{
    "Year_2021": [
        {
            "Dec": "196610",
            "oct": "196699",
            "Sep": "131073",
            "Jul": "122050"
        }
    ]
}

i have tried different possibilities and got the craziest constellations, just not the right one.

My current code:

import csv
import datetime
import time
import os.path
import json
from collections import defaultdict

sys_time = datetime.datetime.now()
format_sys_time = sys_time.strftime('[%Y-%m-%d] %H:%M:%S')      # Other Datetime Format

act_month = int(sys_time.strftime('%m'))
#print act_month

output_json_file    = "/var/www/json/EXP_MONTHLY_POWER_" + sys_time.strftime('%Y') + ".json"

start_time = time.time()    # measure how long a programm run takes

columns = defaultdict(list) # each value in each column is appended to a list

# Help function to build dword
def word_to_dword(val_1, val_2):
    result = val_1
    result |= val_2 << 16
    return result

# Calculate past days of the current month
dates = []
for act_month in range(act_month+1, 1, -1):
    act_month -= 1
    if act_month <=9:
     INPUTFILE= "/var/www/csv/EXP_POWER_" + sys_time.strftime('%Y-0') + str(act_month) + ".csv"
    else:
     INPUTFILE= "/var/www/csv/EXP_POWER_" + sys_time.strftime('%Y-') + str(act_month) + ".csv"
    dates.append(INPUTFILE)

#print(dates)
outputfields = [];

#Delete old file to avoid double entrys
if os.path.exists(output_json_file):
    os.remove(output_json_file)


for dayfile in dates:
    if os.path.exists(dayfile):
        with open(dayfile) as csvdatei:
            mvg_reader = csv.DictReader(csvdatei , delimiter=';')   # read rows into a dictionary format
            for row in mvg_reader:                                  # read a row as {column1: value1, column2: value2,...}
                for (fieldname, value) in row.items():              # go over each column name and value
                    columns[fieldname].append(value)                # append the value into the appropriate list
                                                                    # based on column name

        outfields1=[]

        for value in columns['Power_Value(kwh)']:
        #    print(int(value))
            outfields1.append(int(value))

        # Build Power Value from last values of list
        if (len(outfields1) != 0):
            DL_Actual_Power_Value = outfields1[-1]
        else:
            print("Keine Daten gefunden!")

        compString = ""
        compString = dayfile[28:30]     # Build compString from Filename
        
        switcher = {
                "01": "Jan",
                "02": "Feb",
                "03": "Mar",
                "04": "Apr",
                "05": "May",
                "06": "Jun",
                "07": "Jul",
                "08": "Aug",
                "09": "Sep",
                "10": "Oct",
                "11": "Nov",
                "12": "Dec"
            }        
            
        outputfields.append([switcher.get(compString, "Invalid month"), str(DL_Actual_Power_Value)]       )
             
print(outputfields)


    

export_json_main = {}
export_json_main.clear()
export_KEY = 'Year_' + sys_time.strftime('%Y')      # Name des Keys festlegen 
export_json_main[export_KEY] = []
export_json_main[export_KEY].append(      outputfields    )


    
#jsonStr = json.dumps(outputfields)
#print(jsonStr)
#for keys in (outputfields):
#    print(keys[0])
#export_json_main[export_KEY].append({
#    json.dumps(outputfields)
#})
with open(output_json_file, 'w') as outfile:
    json.dump(export_json_main, outfile, indent=4)

This brings me the following output:

{
    "Year_2021": [
        [
            [
                "Dec", 
                "196610"
            ], 
            [
                "Oct", 
                "196699"
            ], 
            [
                "Sep", 
                "131073"
            ], 
            [
                "Jul", 
                "122050"
            ]
        ]
    ]
}