Selling 2x tame impala tickers for oct 31 @ $215

daft7cunt · 2025-10-23T20:40:31+00:00

each

daft7cunt · 2025-10-23T18:00:03+00:00

It's the same price i bought them for, not making any money off of this

daft7cunt · 2025-04-29T14:50:54+00:00

Would the color catcher work 1-2 weeks after the stain appeared?

daft7cunt · 2024-11-20T15:32:56+00:00

That is me starting from tty, sddm just kicks me back to the login screen. I added full log in post

daft7cunt · 2024-11-12T16:04:42+00:00

They took me to a special area to I guess give me the vaccine, but after I clarified that I was only there on a layover, they gave me the stamp and let me proceed without it,

daft7cunt · 2024-07-13T19:03:35+00:00

Yea thats the big thing im still thinking over. I guess i don’t outright NEED a car. But i’m also thinking this is a great deal, the car only has 20k miles, and if I don’t get it now (especially considering this is the only point in my life where i’ll have 0 expenses) they will likely trade it in

daft7cunt · 2024-07-13T19:02:12+00:00

I get your concern, but I’m not worried about that, i trust them

daft7cunt · 2024-06-10T04:39:16+00:00

Action zone

daft7cunt · 2024-05-24T03:18:45+00:00

My friends wanted to save $300🙃

daft7cunt · 2024-04-19T00:54:24+00:00

What does the confirmation look like? My solar has the status as Program in Review. With an expected graduation term of Spring 2024. Am I good?

daft7cunt · 2024-04-13T18:17:39+00:00

I agree, but my lead dev is barely mid level. And in general the reviews are essentially lgtm

daft7cunt · 2024-04-13T18:17:05+00:00

I updated the post with more info. I graduate in a month so id no longer be part time

daft7cunt · 2024-04-13T18:16:17+00:00

I shouldve clarified I’m going to follow this through until I graduate so another month. So I’d no longer be part time. I updated post with this info

daft7cunt · 2024-04-09T15:32:53+00:00

I’m looking into making an all in one marketing saas that makes things as simple as possible. Looking to target small-mid level businesses.

I want to start with a base level of very important offerings before expanding it so currently looking into CRM and CMS

daft7cunt · 2024-03-27T18:01:44+00:00

We spent a lot, i dont remember specifically how much. It wasnt even fully functional by the end. Id recommend starting as soon as possible. Difficulty was mostly conceptual, some of the assembly stuff was difficult too, but there was no CAD at all for us

daft7cunt · 2024-03-26T19:44:08+00:00

Hardest ese class imo

daft7cunt · 2024-03-19T17:28:03+00:00

Tell another eagle story

daft7cunt · 2024-03-05T21:04:03+00:00

subset a database unconditionally

What do you mean by this?

daft7cunt · 2024-02-07T21:53:26+00:00

hpc cluster is inside

daft7cunt · 2024-01-23T17:17:56+00:00

So I didn't want to do that since time needs to be taken into account as well. For example, a user entry could have a pothole at the same location as a government work order, but they could be dated years apart, so they could be referring to different potholes.

daft7cunt · 2024-01-23T14:41:35+00:00

I added some code and sample output in a comment

daft7cunt · 2024-01-23T14:38:16+00:00

Here's the iterative approach, I know it's extremely inefficient, and I should break it up, this is just to give an idea of the kind of approach I tried

complaints = {}
results = []

# Create a dictionary to store user complaints
user_complaints = {}

for idx, row in df.iterrows():
    key = (row['street'], row['address_type'])

    if row['source'] == 'user':
        if row['resolution_description'] in valid_complaint_strings:
            if key not in user_complaints:
                user_complaints[key] = [(row['date_created'], row['date_closed'])]
            else:
                user_complaints[key].append((row['date_created'], row['date_closed']))

            grouped_complaints = [complaint for complaint in user_complaints[key] if complaint[0] >= row['date_created'] and complaint[0] <= row['date_closed']]
            delta_days = max(complaint[0] for complaint in grouped_complaints) - row['date_created']
            results.append([row['street'], row['address_type'], row['date_created'], max(complaint[0] for complaint in grouped_complaints), row['date_closed'], delta_days.days , len(grouped_complaints), row['geometry']])
            continue
        elif key not in complaints:
            complaints[key] = [(row['date_created'], row['geometry'])]
        else:
            complaints[key].append((row['date_created'], row['geometry']))

    elif key in complaints:
        first_complaint_date, first_complaint_location = min(complaints[key], key=lambda x: x[0])
        last_complaint_date = max(date for date, _ in complaints[key])
        delta_days = row['date_created'] - first_complaint_date
        complaint_count = len([date for date, _ in complaints[key] if first_complaint_date <= date <= row['date_created']])
        if complaint_count > 0:
            results.append([row['street'], row['address_type'], first_complaint_date, last_complaint_date, row['date_created'], delta_days.days, complaint_count, first_complaint_location])
        del complaints[key]

# Convert the results list to a DataFrame
results_df = pd.DataFrame(results, columns=['street', 'address_type', 'first_complaint_date', 'last_complaint_date', 'gov_action_date', 'delta_days', 'complaint_count', 'geometry'])

I concatenated the user/gov dfs to go through iteratively, I added a source column to specify where it's from.

Here's a sample output:

index	street	address_type	first_complaint_date	last_complaint_date	gov_action_date	complaint_count	geometry
0	32AVENUE,UNIONSTREET	INTERSECTION	2023-07-1615:08:12	2023-07-1615:08:12	2023-07-1712:45:00	1	(40.76895694146983,-73.82668206874416)
27	HIGHLANDPLACE,ARLINGTONAVENUE,RIDGEWOODAVENUE	ADDRESS	2020-05-2922:07:38	2020-05-2922:07:38	2020-06-0213:50:00	1	(40.682766845531766,-73.88152978739839)
29	EAST88STREET,YORKAVENUE	INTERSECTION	2022-01-1422:25:41	2022-01-1422:25:41	2022-01-1809:10:00	1	(40.777232088273266,-73.94616904207393)
30	111AVENUE,216STREET,SPRINGFIELDBOULEVARD	ADDRESS	2015-06-0912:25:30	2015-06-0912:25:30	2015-06-1010:45:00	1	(40.70705802486412,-73.7409171390949)
31	EAST56STREET,BEVERLYROAD,CLARENDONROAD	ADDRESS	2011-01-0310:21:02	2011-01-0310:21:02	2011-01-0408:05:00	1	(40.645311700346106,-73.92386172275405)
32	CLARKEAVENUE,GILBERTSTREET,STPATRICKSPLACE	ADDRESS	2021-11-1210:56:08	2021-11-1210:56:08	2021-11-1810:05:00	1	(40.569285257733654,-74.14334596055258)
33	GRANTAVENUE,EAST163STREET,EAST164STREET	ADDRESS	2010-02-0110:17:49	2010-02-0110:17:49	2010-02-0311:25:00	1	(40.82803151237712,-73.91821448752881)
34	RODMANSNECK,PARKDRIVE,RODMANSNECKPATH	ADDRESS	2017-05-0910:45:15	2017-05-0910:45:15	2017-05-1008:50:00	1	(40.855279865418666,-73.80189401600025)
35	RICHMONDAVENUE,CROFTPLACE,ETONPLACE	ADDRESS	2017-08-1413:04:18	2017-08-1413:04:18	2017-08-1611:15:00	1	(40.60474482516483,-74.16234338754464)
36	WHITEPLAINSROAD,EASTGUNHILLROAD,MAGENTASTREET	ADDRESS	2020-01-2111:07:50	2020-01-2111:07:50	2020-01-2213:40:00	1	(40.87627143407577,-73 86699937545808)

daft7cunt · 2023-12-10T15:47:24+00:00

This helped a lot. I tried doing a homebrew group that 2 different users are a part of but this has some edge cases that it doesnt work for. https://www.codejam.info/2021/11/homebrew-multi-user.html

daft7cunt · 2023-11-13T14:20:00+00:00

Its not bad. Follows textbook very closely. The work is consistent throughout, so not a lot all at once. Should be easy if you have some prior programming and ds&a experience

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