How to use the bucket pattern for time-series data

Working with Data Drivers
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1

Hi guys.i want to create time based buckets ,specifically for every hour or more if needed.I read here https://docs.mongodb.com/manual/tutorial/model-time-data/#example about the bucket pattern but i dont know what code to use with python pymongo.My dataset consist of 11 files from 2010-2020 and its about 1.5 millions rows and look like this:

_id:ObjectId("603fb0b7142a0cbb439ae2e1")
    id1:3758
    id6:2
    id7:-79.09
    id8:35.97
    id9:5.5
    id10:0
    id11:-99999
    id12:0
    id13:-9999
    c14:"U"
    id15:0
    id16:99
    id17:0
    id18:-99
    id19:-9999
    id20:33
    id21:0
    id22:-99
    id23:0
    timestamp1:2010-01-01T00:05:00.000+00:00
    timestamp2:2009-12-31T19:05:00.000+00:00

All the attributes change every 5 minute expect id1 which remains the same.The is what i have tried(after proccesing the files and converted them into df):

files =  os.listdir('sampl/')
sorted_files =  sorted(files)

for file in sorted_files:
    df = process_file(file)
    #df.reset_index(inplace=True)  # Reset Index
    data_dict = df.to_dict('records')  # Convert to dictionary

    mycol1.update_many(
        {'nsamples': {'$lt': 12}},
        {
            '$push': {'samples': data_dict },
            '$min': {'first': df['timestamp1']},
            '$max': {'last': df['timestamp1']},
            '$inc': {'nsamples': 1}
        },
        upsert=True
    )

Output:
bson.errors.InvalidDocument: cannot encode object: id1 id6 id7 ... id23 timestamp1 timestamp2
Any help would be appreciated!Thanks in advance!