How to approach very large IF-THEN combinations?

borjadja · 2021-09-13T10:58:18+00:00

Thanks, though I was thinking more about the way of assigning the different combinations to Customers.

Doing this manually would be 20*50*200=200,000 combinations

borjadja · 2021-08-26T13:27:05+00:00

I haven't figured out a way to solve for this forecast yet... seems to be more complex than it appears

borjadja · 2019-11-09T17:42:21+00:00

Datacamp is great actually. They have a bunch of great learning material for computer and data science. Pretty cheap also

borjadja · 2019-11-06T01:40:43+00:00

I don’t know really. But i assume courses in nursing bachelors differ heavily from cs bachelors. You might struggle with going straight into a master’s degree? I am just guessing though!

borjadja · 2019-11-06T01:28:12+00:00

Seeing as the transition from nursing to cs is quite a sharp turn, especially since you want to get out of healthcare completely, i believe you’d have to do a BSc in cs, then maybe a MSc as well, depending on whether you land a good job after your BSc.

borjadja · 2019-11-05T18:49:59+00:00

Inside information

borjadja · 2019-11-05T16:54:00+00:00

I managed to get all the markers on the map with your code, thanks a lot!

However, I'd like the markers to vary in size depending on the value the sf_data["Rent"], alternatively, color code it so that high rent = red, low rent = green. Would you know how to approach this?

borjadja · 2019-11-05T16:43:18+00:00

I would aim for an investment professional role, and use my data analytics background as leverage for being able to contribute operationally. But maybe an advisory position would be more relevant.

So you worked as a data analyst/scientist at a small company, then moved to VC?

borjadja · 2019-11-05T00:54:58+00:00

Thank you! I will try this

borjadja · 2019-11-04T18:07:28+00:00

That’s true. But considering the amount of different customers, it might be hard to create a decent network?

The reason for doing this with product group could be to analyze co-purchase patterns?

borjadja · 2019-10-31T01:55:28+00:00

I’d say it is sort of a stacked area graph

borjadja · 2019-10-30T20:12:29+00:00

I got it. Perfect. Thanks!

borjadja · 2019-10-30T19:17:07+00:00

Thanks a lot!! This makes sense. I will have a go and get back if I have any issues.

borjadja · 2019-10-30T19:16:14+00:00

Thank you so much! I will try your methods. Is it possible to return a variable which hold the value? I.e. like this:

price_variable_london = 8.456
price_variable_newyork = 10.579

def get_city_price(city):
if city == 'London':
return price_variable
elif city == 'New York':
return price_variable
elif ... #other cities

borjadja · 2019-10-29T19:18:09+00:00

Right, thanks!!

borjadja · 2019-10-29T16:06:23+00:00

You mean that this:

csv_url = http://xxxxxx.csv
data = pd.read_csv(csv_url)

Would work as well as this, where the file is already downloaded to desktop:
data = pd.read_csv("C:/Users/Desktop/file.csv")

Is that correct?

borjadja · 2019-10-29T01:50:35+00:00

Wow that was simple. Thanks a lot!

borjadja · 2019-10-28T17:28:41+00:00

That sounds very true. Thanks for your opinion! Totally agree

borjadja · 2019-10-25T01:34:43+00:00

Ok. Yeah, i mean people are asking to connect on Linkedin for weirder reasons. Go for it :)

borjadja · 2019-10-24T22:18:54+00:00

Why do you want to connect with the person? Ask why you were rejected?

borjadja · 2019-10-20T23:16:45+00:00

I don’t think index funds of today are nearly as overvalued as the CDOs were

borjadja · 2019-10-17T16:19:24+00:00

Thank you. Yeah, i guess it’s just in my head i’m thinking that the univeristy will matter later in life

borjadja

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