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There are others but this example will get the point across
https://www.hackerrank.com/challenges/collections-counter/problem
The constraints say: 20 < price < 100 and 2 < shoe_size < 20 which means price does not include 20 or 100 and shoe_size does not include 2 or 20 ... so why in their testing data do they require that you include this invalid data for you to get the "correct" answer?
Note: The data which includes this is in a data_set, answer pair I bought to try and figure out why I was not passing all of the tests.
Answer provided via IRC at bhansa's suggestion. The guy/gal that answered wasn't associated with hackerrank but (s)he suggested to report it as an issue and this was not supposed to be a normal behavior regardless of how frequently I have seen it pop up.
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I have a dataset with a column containing strings in multiple languages. I am hoping to remove rows where one column contains a string in any language other than English. I can't seem to find any way to go about this. Does anyone have suggestions for a library or code that might be useful for this purpose?
This seems like a repeat of this, as the root of this question is how to detect non-English languages rather than how to filter a dataset.
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Can anyone point me to a tool (preferably in python or c++) to solve an optimization problem where in the objective has power fractions such as :
Maximize x1^0.2 + x2^ 0.3 + x3^0.4
Thanks
I think this should be possible in python with scipy.optimize
Since it allows fractional exponentiation
4**0.5 = 2
4**0.2 = 1.3195079
and the objective function is defined as a plain python function.
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Closed 2 years ago.
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I want to forecast upcoming total users on a daily basis within Python using a machine learning algorithm. Check the pattern below:
Looking at this graph, I was wondering if someone knows which forecasting method in Python I should use to predict?
Thanks!
If you have no additional data expect the user data over time which you have shown, the only thing you can do is try to find a function dependent on time which gives you a good approximation for that plot (ordinary curve fitting). I suppose that's not what you want.
To do a predection (which can be done not only by a machine learning approach), you need other data which is somehow correlated to the data you want to predict.
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Closed 8 years ago.
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I am looking for an implementation of Continuous Wavelet Transform for Python that includes Haar Wavelet.
I would like to reproduce the experiment given by MathWorks for Matlab, at this link.
I tried with Pyscellania but I obtain completely different coefficients.
Is there a Python implementation of the CWT out there that includes the Haar Wavalet apart from Pyscellania?
Your request is clear.
Have you tried Pyscellania's normalised or standard Haar Wavelet?
Maybe you are just using the wrong one.
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Closed 7 years ago.
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Is anyone aware of a pure python implementation of BLAST alignment? I am trying to study this algorithm...
In fact a complete implementation of the BLAST algorithm is a quite hard. It has a lot of steps and optimizations. What could you do is: take a look of the BLAST Book from O'Reilly, for a very good explanation, take a look of the NCBI Blast code base, that it is big and hard to understand at the first glace, or, I sugest you to take a look at other BLAST implementation or may be, others algorithms like BLAT and Genoogle (http://genoogle.pih.bio.br/)
Try looking into BioPython:
http://biopython.org/
http://github.com/JoaoRodrigues/biopython/tree/GSOC2010