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Difference between getContext() , getApplicationContext() , getBaseContext() and “this”
...| NO¹ | NO¹ |
| Layout Inflation | NO² | YES | NO² | NO² | NO² |
| Start a Service | YES | YES | YES | YES | YES |
| Bind to a Service | YES | Y...
The most efficient way to implement an integer based power function pow(int, int)
...n chain for a¹⁵ above, the subproblem for a⁶ must be computed as (a³)² since a³ is re-used (as opposed to, say, a⁶ = a²(a²)², which also requires three multiplies).
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How can I get list of values from dict?
... ± std. dev. of 7 runs, 1000000 loops each)
Big Dict(str)
17.5 ms ± 142 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
16.5 ms ± 338 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
16.2 ms ± 19.7 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
Big Dict(float)
...
Getting key with maximum value in dictionary?
...came with same performance on my machine on python 2.7. Testing: f1 - 18 µs per loop Testing: f2 - 33.7 µs per loop Testing: f3b - 50 µs per loop Testing: f4b - 30.7 µs per loop Testing: f5 - 28 µs per loop Testing: f6 - 23 µs per loop Testing: f7 - 18 µs per loop Testing: f8 - 43.9 ...
Get list from pandas DataFrame column headers
...he difference in performance is obvious:
%timeit df.columns.tolist()
16.7 µs ± 317 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
%timeit df.columns.values.tolist()
1.24 µs ± 12.3 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
For those who hate typing, you can...
Find integer index of rows with NaN in pandas dataframe
... df.loc[pd.isna(df['b']), :].index
And their corresponding timings:
333 µs ± 9.95 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
280 µs ± 220 ns per loop (mean ± std. dev. of 7 runs, 1000 loops each)
313 µs ± 128 ns per loop (mean ± std. dev. of 7 runs, 1000 loops each)
6.84 ...
Can Python test the membership of multiple values in a list?
...(range(50000))
>>> %timeit bigset >= bigsubset
1.14 ms ± 13.9 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
>>> %timeit all(x in bigset for x in bigsubset)
5.96 ms ± 37 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
Using subset testing is still fas...
Find nearest value in numpy array
...n. I wonder why it is so slow anyways. Plain np.searchsorted takes about 2 µs for my test set, the whole function about 10 µs. Using np.abs it's getting even worse. No clue what python is doing there.
– Michael
Feb 17 '15 at 18:07
...
Is it possible to use argsort in descending order?
...00)
>>> n = 30
>>> timeit (-avgDists).argsort()[:n]
1.93 µs ± 6.68 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
>>> timeit avgDists.argsort()[::-1][:n]
1.64 µs ± 3.39 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
>>> timeit avg...