You could do it fairly succinctly by using a csv.DictWriter.
import csv
my_dict = {
              "2020-09-03": {
                  "1. open": "128.1900",
                  "2. high": "129.9500",
                  "3. low": "123.6500",
                  "4. close": "124.4500",
                  "5. volume": "5716750"
              },
              "2020-09-02": {
                  "1. open": "123.7200",
                  "2. high": "123.567",
                  "3. low": "123.6500",
                  "4. close": "128.3450",
                  "5. volume": "6745450"
              },
          }
filename = 'converted_dict.csv'
fieldkeys = ['1. open', '2. high', '3. low']
fieldnames = [fieldkey.split()[1] for fieldkey in fieldkeys]
fieldmap = dict(zip(fieldnames, fieldkeys))
with open(filename, 'w', newline='') as file:
    writer = csv.DictWriter(file, ['date'] + fieldnames)
    writer.writeheader()  # If desired.
    for date, values in my_dict.items():
        row = {fieldname: values[fieldmap[fieldname]] for fieldname in fieldnames}
        writer.writerow(dict(date=date, **row))
Resulting CSV file's contents:
date,open,high,low
2020-09-03,128.1900,129.9500,123.6500
2020-09-02,123.7200,123.567,123.6500