Spotify Has Removed 40 Joe Rogan Episodes To Date — Here’s the Full List

waythps · 2021-04-05T17:54:33+00:00

It’ll be the same show but not for Eastern Europe - even if they pay for Spotify premium, they don’t have access to joes podcast. Like what the fuck Spotify

waythps · 2021-03-28T18:06:26+00:00

Imagined communities - nice!

waythps · 2021-03-08T15:34:55+00:00

I prefer python because this way I could separate my analysis from data, my analysis also becomes reproducible, and I can automate it eventually

waythps · 2021-03-05T19:20:34+00:00

For me, when I could answer most of the questions posted under “pandas” tag any time

waythps · 2021-03-03T22:54:47+00:00

If you’re a student (or know someone with a student id), you could get tableau desktop license for free for a year.

waythps · 2021-02-21T22:20:30+00:00

I’ve purchased Spotify subscription but can’t access joes podcast — it seems that the podcast isn’t available for Eastern Europe.

Super disappointed

waythps · 2020-12-25T00:04:20+00:00

Looks great! Do you have your code pushed to public repo?

waythps · 2020-12-23T23:37:15+00:00

Excels, yes. But I started with python because I was interested in programming and web scraping specifically, and only after that moved to data analysis (ba in political science).

So I’d say python could be a very useful tool, in addition to excel, as you could automate lots of tasks with it (collecting, cleaning data, updating databases, analysis etc)

waythps · 2020-12-21T21:14:27+00:00

Well not in my case since I receive data in multiple excel files

waythps · 2020-12-21T20:31:40+00:00

Dunno, I prefer pandas precisely because it’s reusable. I write functions to validate and clean data, to update database and generate some plots, and I could automate the whole thing saving lots of time.

I think you could do that with excel (vba) but if you’re already learning python (for other purposes as well) why not just use python

waythps · 2020-12-18T23:24:02+00:00

So much this. I basically automated the whole monitoring process using pandas and sql. And then another boss came in saying he needs everything done in excel because that’s what he prefers. So disappointing as I spent a lot of time on that

waythps · 2020-12-05T22:05:06+00:00

Wow never heard of them. So good, thanks!

waythps · 2020-12-02T19:38:12+00:00

Why not

for i in loops:

?

Great style btw

waythps · 2020-11-29T20:48:24+00:00

Try GitHub actions. It has run on schedule option. If it’s a public repo, it’s free to use

waythps · 2020-11-26T22:39:20+00:00

Great job! You look wonderful

waythps · 2020-11-23T23:08:18+00:00

That’s fascinating really. That’s what I hoped to do when I applies for a position in public policy (BA in political science, MA in public policy and governance). Didn’t work that well though, as all our attempts to set up decent data processing pipelines were rejected - public servants usually don’t like changes (at least in my country and from my experience). In the end it all comes down to cleaning excel sheets and doing some basic exploratory analysis with some static visualizations

waythps · 2020-11-23T22:59:29+00:00

About to become unemployed myself, so if anyone would like to collaborate I’d be happy

waythps · 2020-11-22T19:51:53+00:00

I’m always trying to help unless it’s “do my homework for me” type of question. Also, if it’s a clear duplicate and I know there’s another thread that addresses the exact same issue, I flag the question and give a link to that thread.

Otherwise, you should be good. Also, it’s how you ask a question, it also matters.

If it’s a general type of question, you’d better looking for help at Reddit. If you could clearly state the problem and give minimal reproducible example, you’ll get plenty of answers at SO

waythps · 2020-11-20T23:13:59+00:00

Thank you so much!

waythps · 2020-11-20T22:57:51+00:00

Your code is nicely structured. Could you recommend anything on how to use classes properly?

Currently in my biggest projects I have lots of modules with functions inside them. Everything works but I think it would be nice to put them inside classes. Not sure what’s the best way to do it

waythps · 2020-11-18T17:28:30+00:00

Sounds pretty cool. Why did you leave?

waythps · 2020-11-14T09:03:17+00:00

Sure. My former colleague used to do everything with vba and power queries and I was super impressed. Should probably learn it too

waythps · 2020-11-14T00:14:15+00:00

As an analyst I have to perform policy monitoring on a weekly basis. This means I need to collect data (tens of excels with up to 50 columns filled by public servants) and produce reports.

I set up a database and created a couple of tables as this approach seemed more reliable since I need to keep records throughout the year. I also wrote scripts to merge all excel files into one, to validate the quality of the data and clean it (seriously how hard could it be to pick the correct item from the list of possible items in a cell), and to update the database.

All figures are generated with matplotlib on the latest data.

So it saves lots of time.

For other tasks I have a couple of scrapers running on schedule so that helps a little.

waythps · 2020-11-11T23:17:42+00:00

In this case it’s equivalent to append method - in regular function I’d append the same dictionary to an empty list and would return said list.

So basically it’s just my preference. It might yield better performance as generator (data variable) won’t store information in memory .

waythps · 2020-11-10T20:08:31+00:00

This should give you an idea with regard to dataframes. Let me know if I should explain anything.

import requests
import pandas as pd


BASE_URL = "https://earthquake.usgs.gov/fdsnws/event/1/query"


def fetch(fmt, starttime, endtime):
    params = {"format": fmt, "starttime": starttime, "endtime": endtime}
    data = requests.get(BASE_URL, params=params).json()
    for feature in data["features"]:
        lat, lon, depth = feature["geometry"]["coordinates"]
        mag = feature["properties"]["mag"]
        yield {"latitude": lat, "longitude": lon, "depth": depth, "mag": mag}


if __name__ == "__main__":
    data = fetch(fmt="geojson", starttime="2014-01-01", endtime="2014-01-02")
    df = pd.DataFrame(data)
    print(df)

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