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You can get a list of all possible words (including the nouns, verbs, adjectives and so on) by using a comprehension. This loops over all elements of a sequence, as with a for-loop, but can be faster. …

Most of the code you provided doesn't do much to help your actual problem of renaming the files. I will just focus on tha tpart by showing you how to get the filenames you want. You can rename the fi …

I would probably just pass a parameter for the distribution name and then a set of parameters in a Python dictionary. …

It seems you are passing the same parameters to both Python classes: ARIMAX and SARIMAX... and this should produce the same answer, I agree. …

I would suggest using a Pandas DataFrame (you didn't mention it in your question). Then it would be as simple as the following Create the dataframe from you list x, calling the single column x: In …

Assuming that example is working for you, trying to write the data every 3 seconds, you need to just change the scheduling to be schedule.every(1).hour.do(write_to_excel) You are currently writing …

Have a look into KD-Trees. They work by partitioning your space into discrete blocks, via a (wait for it...) tree. Here is the wikipedia example for a 3d space: Each of the cuboids is represented b …

Assuming you have the ground truth results y_true and also the corresponding model predictions y_pred, you can use SciKit-Learn's precision_recall_fscore_support. from sklearn.metrics import precision …

You get a view of the matrix, with only the the axes transposed. So your B doesn't get transposed. More nuances depend on the shape of your original array: In [1]: import numpy as np In [2]: np.nda …

If you know there are only specific variants, you can obviously make a look-up table yourself (i.e. a Python dictionary). Otherwise you could try using a fuzzy matching library, like fuzzywuzzy. …

Because on each loop you assign a single value to the entire column: tots_df['orc_4_totals'] = s4 # entire column orc_4_totals = s4! (the same thing for the other column. It equals all ones the …

This seems about right. You can use SciKit learn quite easily, as the predictions and test results you have should all be in NumPy arrays anyway. Take a look at the regression metrics. The metrics yo …

Here is an example where I create a new row called Other, which contains the sum of all values below a given threshold. I then remove the rows that were below that threshold (and so included in the s …

I would recommend breaking the problem down a little bit to reduce the memory usage at any one time. The first part of your main function gets the IDs using getIDList. That seems fine, so leave it th …

Here is a nice example tutorial if you're new to profiling in Python. You can use cProfile, a built-in python module. … You can do this in the terminal quite simply (if your script is designed to be run that way) by running: python -m cProfile -o profiling_results.prof your_script.py In words (flags shown in bold): python …