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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
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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...
How to calculate moving average using NumPy?
...an ± std. dev. of 7 runs, 1 loop each)
scipy.convolve :
1.07 ms ± 26.7 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
scipy.convolve, edge handling :
4.68 ms ± 9.69 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
numpy.cumsum :
5.31 ms ± 5.11 µs per loop (mean ± s...
Set value for particular cell in pandas DataFrame using index
...
In [18]: %timeit df.set_value('C', 'x', 10)
100000 loops, best of 3: 2.9 µs per loop
In [20]: %timeit df['x']['C'] = 10
100000 loops, best of 3: 6.31 µs per loop
In [81]: %timeit df.at['C', 'x'] = 10
100000 loops, best of 3: 9.2 µs per loop
...
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...
How to remove \xa0 from string in Python?
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Not so sure, you may want normalize('NFKD', '1º\xa0dia') to return '1º dia' but it returns '1o dia'
– Faccion
Nov 8 '17 at 14:58
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