大约有 800 项符合查询结果（耗时：0.0106秒） [XML]
Numpy: find first index of value fast
...e(100000)
%timeit index(arr, 5) # 1000000 loops, best of 3: 1.88 µs per loop
%timeit find_first(5, arr) # 1000000 loops, best of 3: 1.7 µs per loop
%timeit index(arr, 99999) # 10000 loops, best of 3: 118 µs per loop
%timeit find_first(99999, arr) # 10000 loops, best of 3: 9...
Is there a way to make R beep/play a sound at the end of a script?
...ered Jul 1 '14 at 18:08
Rasmus BååthRasmus Bååth
3,62222 gold badges2121 silver badges2525 bronze badges
...
Remove rows with duplicate indices (Pandas DataFrame and TimeSeries)
...>> %timeit df3.groupby(df3.index).first()
1000 loops, best of 3: 580 µs per loop
>>> %timeit df3[~df3.index.duplicated(keep='first')]
1000 loops, best of 3: 307 µs per loop
Note that you can keep the last element by changing the keep argument to 'last'.
It should also be noted tha...
Approximate cost to access various caches and main memory?
... Mutex lock/unlock
100 ns Main memory (RAM)
2 000 ns (2µs) 1KB Zippy-compress
Still some improvements, prediction for 2020
16 000 ns (16µs) SSD random read (olibre's note: should be less)
500 000 ns (½ms) Round trip in datacenter
2 000 000 ns (2ms) HDD random read (s...
What is your preferred style for naming variables in R? [closed]
...ered Nov 16 '12 at 8:55
Rasmus BååthRasmus Bååth
3,62222 gold badges2121 silver badges2525 bronze badges
...
Add single element to array in numpy
...
for k in range(int(10e4)):
d.append(k)
f = np.array(d)
13.5 ms ± 277 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
Pre-allocating numpy array:
e = np.zeros((n,))
for k in range(n):
e[k] = k
9.92 ms ± 752 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
When the...
pypi UserWarning: Unknown distribution option: 'install_requires'
...ed Nov 28 '11 at 15:38
Fredrik HåårdFredrik Håård
2,4622020 silver badges3232 bronze badges
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Delete rows from a pandas DataFrame based on a conditional expression involving len(string) giving K
...than raw column based filtration:-
%timeit df_new = df[(df.E>0)]
345 µs ± 10.5 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
%timeit dft.drop(dft[dft.E < 0].index, inplace=True)
890 µs ± 94.9 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
A column is basical...
Efficiently replace all accented characters in a string?
...
"à":"a",
"ả":"a",
"ȃ":"a",
"ā":"a",
"ą":"a",
"ᶏ":"a",
"ẚ":"a",
"å":"a",
"ǻ":"a",
"ḁ":"a",
"ⱥ":"a",
"ã":"a",
"ꜳ":"aa",
"æ":"ae",
"ǽ":"ae",
"ǣ":"ae",
"ꜵ":"ao",
"ꜷ":"au",
"ꜹ":"av",
"ꜻ":"av",
"ꜽ":"ay",
"ḃ":"b",
"ḅ":"b",
"ɓ":"b",
"ḇ":"b",
"ᵬ":"b",
"ᶀ":"b",
"ƀ"...
What IDE to use for Python? [closed]
...| |*very limited
Gedit |Y |F |Y¹|Y | | | |Y |Y |Y | | |Y²| | | | |¹with plugin; ²sort of
Idle |Y |F |Y | |Y | | |Y |Y | | | | | | | | |
IntelliJ |Y |CF|Y |Y |Y |Y |Y |Y |Y |Y |Y |Y |Y |Y |Y |Y |Y |
JEdit |Y |F | |Y | | | | |...