Ordering and filtering data from csv.dictreader

Question

import csv

with open ('data_airbnb.csv', newline='') as f:
    reader = csv.DictReader(f, delimiter = ',')
    data_list = list(reader)

The below is 1 sample data_list content:

[OrderedDict([('room_id', '3179080'), ('survey_id', '1280'), ('host_id', '15295886'), ('room_type', 'Shared room'), ('country', ''), ('city', 'Singapore'), ('borough', ''), ('neighborhood', 'TS17'), ('reviews', '15'), ('overall_satisfaction', '5.0'), ('accommodates', '12'), ('bedrooms', '1.0'), ('bathrooms', ''), ('price', '77.0'), ('minstay', ''), ('last_modified', '2017-05-17 09:10:24.216548'), ('latitude', '1.310862'), ('longitude', '103.858828'), ('location', '0101000020E6100000E738B709F7F659403F1BB96E4AF9F43F')])

Dear friends, Im trying to retrieve the top 10 priciest room (price) with room_id and put them into a list from the data_list which contains thousands of rows. the sample list I shown was 1 row of it?

I have tried it before for a simple list but I have been receiving error accessing the values for this and do not know how to do it.

please advice. Thanks

Answer 1

One way is to sort your list of dictionaries and select the first 10 elements. You can achieve this via sorted and a custom function:

res = sorted(data_list, key=lambda x: float(x['price']), reverse=True)[:10]

Explanation

• lambda represents an anonymous function; you could alternatively use an explicit named function with the same logic.
• float conversion is necessary to avoid comparing strings, which are currently used to represent prices in your OrderedDict objects.
• reverse=True ensures we are ordering by highest price first.
• Since sorted returns a list, you can use regular list slicing via [:10] to extract the first 10 elements.