大约有 900 项符合查询结果（耗时：0.0101秒） [XML]
Why isn't my Pandas 'apply' function referencing multiple columns working? [closed]
... that an intermediate result is being cached. 1000 loops, best of
3: 481 µs per loop
Example 2: vectorize using pandas.apply():
%%timeit
df['a'] % df['c']
The slowest run took 458.85 times longer than the fastest. This could
mean that an intermediate result is being cached. 10000 loops...
Add spaces before Capital Letters
Given the string "ThisStringHasNoSpacesButItDoesHaveCapitals" what is the best way to add spaces before the capital letters. So the end string would be "This String Has No Spaces But It Does Have Capitals"
...
iPhone: How to get current milliseconds?
...if portability is a priority for you.
iPhone 4S
CACurrentMediaTime: 1.33 µs/call
gettimeofday: 1.38 µs/call
[NSDate timeIntervalSinceReferenceDate]: 1.45 µs/call
CFAbsoluteTimeGetCurrent: 1.48 µs/call
[[NSDate date] timeIntervalSince1970]: 4.93 µs/call
iPad 3
CACurrentMediaTime: 1.25 µs/c...
How to compare Unicode characters that “look alike”?
...ain(string[] args)
{
char first = 'μ';
char second = 'µ';
// Technically you only need to normalize U+00B5 to obtain U+03BC, but
// if you're unsure which character is which, you can safely normalize both
string firstNormalized = first.ToString().Normal...
Insert an element at a specific index in a list and return the updated list
...ents for Python 3.4.5:
Mine answer using sliced insertion - Fastest (3.08 µsec per loop)
mquadri$ python3 -m timeit -s "a = list(range(1000))" "b = a[:]; b[500:500] = [3]"
100000 loops, best of 3: 3.08 µsec per loop
ATOzTOA's accepted answer based on merge of sliced lists - Second (6.71 µsec...
“Cloning” row or column vectors
...t;>> %timeit np.array(np.broadcast_to(x, (reps, n)))
10.2 ms ± 62.3 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
>>> %timeit np.repeat(x[np.newaxis, :], reps, axis=0)
9.88 ms ± 52.4 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
>>> %timeit np.ti...
Python dictionary: Get list of values for list of keys
...imeit map(lambda _: m[_], l) # using 'map'
1000000 loops, best of 3: 1.66 µs per loop
In[5]: %timeit list(m[_] for _ in l) # a generator expression passed to a list constructor.
1000000 loops, best of 3: 1.65 µs per loop
In[6]: %timeit map(m.__getitem__, l)
The slowest run took 4.01 times longer...
Return multiple columns from pandas apply()
...best of 3: 2.61 ms per loop
Return tuple:
1000 loops, best of 3: 819 µs per loop
share
|
improve this answer
|
follow
|
...
SQL Server: Make all UPPER case to Proper Case/Title Case
...---------
All Upper Case and Some lower Ää Öö Üü Éé Øø Cc Ææ
share
|
improve this answer
|
follow
|
...
How to select rows from a DataFrame based on column values?
...imeit mask = df['A'].values == 'foo'
%timeit mask = df['A'] == 'foo'
5.84 µs ± 195 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
166 µs ± 4.45 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)
Evaluating the mask with the numpy array is ~ 30 times faster. This is pa...