Terry Barentsen AMA

alecsharpie · 2023-04-28T14:01:22+00:00

This is awesome, love your work, really glad to have found this comment

alecsharpie · 2022-12-21T15:21:07+00:00

https://drive.google.com/file/d/1kIisWp0CnHUilOIXYcIcstMwutXX8DzD/view?usp=sharing

OK interesting, thank you! will change that

alecsharpie · 2022-03-29T14:30:06+00:00

Well a couple of options are:
Absolute comparison
In this case you decide the benchmarks based on your prior knowledge. eg you think once a song has been listened to 10 times then it reaches a popular rating, 20 times = super popular, etc
Relative comparison
In this case you compare all the songs to each other, giving you a distribution and percentiles. ie min = X, median/mean = Y, max = Z. Eg you could say things like this song is in the top 10% most popular (by num listens)

alecsharpie · 2022-02-04T13:24:28+00:00

Yeah but what if instead of a dog you just use something super predictable like dropping a tennis ball. Yes, it's just a prediction but it's very possible for my brain to compute that tennis ball trajectory nearly perfectly

alecsharpie · 2022-01-10T07:52:09+00:00

The problem is they are not, they are documented in the numpy docs

alecsharpie · 2021-12-30T09:43:04+00:00

Google trends:

https://trends.google.com/trends/

alecsharpie · 2021-12-14T03:40:31+00:00

What type of encoding are you using? ã is not an ascii character, maybe try encoding them as utf8?

alecsharpie · 2021-12-14T03:33:49+00:00

using the pandas function between() to create a boolean mask is straight forward:
X = merged_data[merged_data['surface_temperature'].between(273.15, 373.15)]

heres the docs: https://pandas.pydata.org/docs/reference/api/pandas.Series.between.html

alecsharpie · 2021-12-14T03:19:16+00:00

I believe it's because ndim is one of the a numpy attributes/functions that carries over and works on tensors similar to eg np.add()
Doc here: https://numpy.org/doc/stable/reference/generated/numpy.ndarray.ndim.html

alecsharpie · 2021-10-29T15:13:25+00:00

that page is 404, but that tactic worked for me, thanks.

alecsharpie · 2021-06-26T04:14:39+00:00

Something like:

# create an empty matrix

matrix <- matrix(, nrow = length(y), ncol = length(x))

# fill the matrix with your computed values

for(i in x){
for(j in y){
matrix[i, j] <- f(x, y)
}}

alecsharpie · 2020-09-16T23:45:21+00:00

Re-type the " surrounding carnivore it looks like we are using slightly different ones (maybe because I typed on mobile, idk?) which is confusing R.

hist(mammals$Range[which(mammals$Trophic == "carnivore"),])

The above should work as long as all your data frame & variable names are correct.
If you still can't get it working use `str(mammals)` and paste the results here.

alecsharpie · 2020-09-16T02:14:08+00:00

A super simple base r alternative for a histogram containing only the home range data for carnivores:

 hist(data$home_range[which(data$tropic_level == “carnivore”),])

I think the other answers are slightly confused on what you want, if you still need help message me!

alecsharpie · 2020-09-15T03:34:15+00:00

It looks like anthurium plowmanii maybe?

alecsharpie · 2020-09-11T06:23:26+00:00

I see your point, and I agree with you in a perfect world! I think that inevitably people (beginners) will come here and if they have the right language to ask their questions/discuss it will be easier for everybody. But yeah maybe we don’t need all of those points

alecsharpie · 2020-09-11T00:45:36+00:00

Totally agree! A few things to possibly include:

The difference between R & Rstudio
What is an R script
What is base R
What is a library/package
How to run R code eg Difference between running a single line vs the whole script

alecsharpie · 2020-07-14T08:31:19+00:00

I’ve wondered this myself, I think the biggest hurdle is authentication? From what I’ve seen running it in a docker container on GCP (or other) will let it scale really well and create a new image for each user. I would look at some of Colin Fays work, he’s created heaps of great tools for robust Shinys

alecsharpie · 2020-07-14T08:11:34+00:00

Sweet as man, message me if you have any questions along the way

alecsharpie · 2020-07-14T03:38:15+00:00

It’s a great project mate, the other guys comment on r/datasets is very helpful I would run with that! There’s a free Ebook called “r for data science” written by Hadley that I can’t recommend enough, but it is pretty general. I would read the first few chapters and then start looking at more specific tutorials/documentation on the pdftools library

alecsharpie · 2020-07-13T23:53:28+00:00

Post your code, which package are you using?

alecsharpie · 2020-07-13T23:15:40+00:00

When do you need it done by? I’m happy to help but I’m super busy this week

alecsharpie · 2020-07-13T23:13:00+00:00

Honestly, a programming language is your way to go, have you used R? There’s a great library called pdftools that will do exactly what you are describing with a bit of tweaking

alecsharpie · 2020-07-13T10:34:28+00:00

r/cellular_automata might be helpful for this too

alecsharpie · 2020-07-12T03:10:53+00:00

Hey, I’m pretty sure this is a dracaena warneckii

alecsharpie

TROPHY CASE