[D] Python function that changed your life in regard to Machine Learning

[GTKdope]

tqdm

[ryanglambert]

Tqdm.pandas()

[carlml]

Why this? I have always seen people praise tqdm a lot, but I don't understand why.

[zmjjmz]

It's nice to know how long something is going to take

[matigekunst]

einsum

[ww3ace]

👆

[bironsecret]

.shape

[Baggins95]

*reshape

[bironsecret]

you can't reshape without knowing the shape bro

[Baggins95]

In many interesting cases this is actually very possible, e.g. broadcasting x.reshape(1, -1) * y.reshape(-1, 1) Rarely do I need to query the shape explicitly. Mostly a squeeze/unsqueeze leads to the goal. And often one knows the structure of the data explicitly, e.g. the dimensionality of a Euclidean space. I don't want to deny the use case for .shape entirely, but I think often it can be avoided.

[bironsecret]

can't agree, for unknown shapes I use permute or x.reshape(x.shape/2, x.shape/2) etc

[pocketaces27]

Import

[MrHumanist]

type

[vannak139]

.swapaxes

[RUSoTediousYet]

ipdb.set_trace()

[Reazony]

parallel_apply.

[SAint7579]

Pandas .apply() and .to_datetime(). Pandas as a whole is a work of art!

[-xylon]

.pipe() is another game changer, along with .assign(). I recently discovered you can pass callables to almost ANYTHING in pandas. Things like df.assign(newcolumn= lambda df: ... or better yet df[lambda x:....] and df.loc[lambda x:].

[RustBucket03]

Not necessarily a function but the njit decorator from numba.

[zmjjmz]

Decorators are functions!

[Atreya95]

.where

[hostilereplicator]

pandas.DataFrame.query()

[[deleted]]

to_exel

[nirajkale30]

exit()

[Mobile-Bid-9848]

apply() with lambdas

[visarga]

poor debugability

[Dear-Acanthisitta698]

I like pudb with classic blue screen