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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def parse_changes(json):
 """ Gets price changes from JSON Args: json: JSON data as a list of dict dates, where the keys are the raw market statistics. Returns: List of floats of price changes between entries in JSON. """

    changes = []
    dates = len(json)
    for date in range(1, dates): 
        last_close = json[date - 1]['close']
        now_close = json[date]['close']
        changes.append(now_close - last_close)
    logger.debug('Market Changes (from JSON):\n{0}'.format(changes))
    return changes