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Editorial Team
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Asked: 2026-05-25T11:23:39+00:00

I’m reading a csv file, using DictReader(). The function returns a dictionary, where the

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I’m reading a csv file, using DictReader(). The function returns a dictionary, where the header items are the keys and the cells are the values. Pretty cool.

But I’m trying to account for rows where the data may not be what I expect it to be. In that case (I’m catching a ValueError exception), I would like the rows that are ‘suspect’ to go into a separate dictionary, for manual processing.

My question is this: since my first dictionary (the object returned by DictReader) has all of its keys set up properly, how do I copy just the keys into my second dictionary, the one which I want to be just a dictionary of suspect rows, to be manually processed?

I’ve been toying around with dict.fromkeys() and such for a while now and I’m just not getting anywhere. Halp!

EDIT: Pasting some of my erroneous code. Going to go hide in shame of my code. Don’t judge me! 😉

unsure_rows = dict.fromkeys(dict(csv_reader).keys(), [])
for row in csv_reader:
#   if row['Start Time'] != 'None':
    try:
        if before_date > strptime(row['Start Time'], '%Y-%m-%d %H:%M:%S') > after_date:
            continue
    except ValueError:
        unsure_rows += row

ValueError: dictionary update sequence element #0 has length 13; 2 is required

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1 Answer

  1. Editorial Team

    You are close. Try:

    dict.fromkeys(my_csv_dict.keys(),[])

    This will initialize a dictionary with the same keys that you parsed from your CSV file, and each one will map to an empty list (to which, I assume, you will append your suspect row values).

    Try this. (There are several subtler changes here that are all necessary, like how you can’t initialize unsure_rows before you start reading the CSV.)

    unsure_rows = None
for row in csv_reader:
#   if row['Start Time'] != 'None':
    try:
        if before_date > strptime(row['Start Time'], '%Y-%m-%d %H:%M:%S') > after_date:
            continue
    except ValueError:
        if not unsure_rows:
            # Initialize the unsure rows dictionary
            unsure_rows = dict.fromkeys(csv_reader.fieldnames,[])
        for key in unsure_rows:
            unsure_rows[key].append(row[key])
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