如何从字典中的列表中删除所有非数值？

Question

I hope the question wasn't too confusing. I have made a little webscraper that scrapes a website for real estate informaton (price, size (square meters), number of bedrooms etc.). I have stored these pieces of information in a dictionary of lists, where each index represents each real estate listing, like this:

info_dict = {prices: ["1200000", "1400000", "1000000", "-"], sizes = ["120", "140", "90", "100"], bedrooms = ["2", "3", "2", "1"]}

My problem is that I'm going to do analysis on this information, ie price per square meter etc. And some of my values are not formatted right, like index 3 in info_dict["prices"]. For non numerical values like this I want to remove this value from the dictionary as well as the other values for this index (sizes, bedrooms). Any ideas on how I can accomplish this?

Answer 1

You could get the valid triplets and then build another dictionary of use them directly.

>>> res = [(x,y,z) for x,y,z in zip(*info_dict.values()) if x.isdigit()]
>>> res
[('1200000', '120', '2'), ('1400000', '140', '3'), ('1000000', '90', '2')]

Answer 2

There are bunch of different ways. One of the approaches is to use regular expressions.

import re

digit_pattern = re.compile('\d+')

info_dict = {"prices" : ["1200000", "1400000", "1000000", "-"], "sizes":["120", "140", "90", "100"], "bedrooms": ["2", "3", "2", "1"]}

pattern_info_dict = {key:[rec for rec in value if digit_pattern.match(str(rec))] for key, value in info_dict.items()}

pattern_info_dict
{'prices': ['1200000', '1400000', '1000000'],
 'sizes': ['120', '140', '90', '100'],
 'bedrooms': ['2', '3', '2', '1']}

If in future the pattern changes, you would just need to change the pattern and the code should still work fine.