大约有 46,000 项符合查询结果（耗时：0.0444秒） [XML]
How to check whether a pandas DataFrame is empty?
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505
You can use the attribute df.empty to check whether it's empty or not:
if df.empty:
print(...
Peak signal detection in realtime timeseries data
...core at which the algorithm signals and influence = the influence (between 0 and 1) of new signals on the mean and standard deviation. For example, a lag of 5 will use the last 5 observations to smooth the data. A threshold of 3.5 will signal if a datapoint is 3.5 standard deviations away from the m...
How to remove the first Item from a list?
I have the list [0, 1, 2, 3, 4] I'd like to make it into [1, 2, 3, 4] . How do I go about this?
10 Answers
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What is the difference between exit(0) and exit(1) in C?
Can anyone tell me? What is the difference between exit(0) and exit(1) in C language?
11 Answers
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Check substring exists in a string in C
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280
if(strstr(sent, word) != NULL) {
/* ... */
}
Note that strstr returns a pointer to the sta...
What ports does RabbitMQ use?
...|
edited Sep 19 '14 at 18:00
Eric Leschinski
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What does (x ^ 0x1) != 0 mean?
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The XOR operation (x ^ 0x1) inverts bit 0. So the expression effectively means: if bit 0 of x is 0, or any other bit of x is 1, then the expression is true.
Conversely the expression is false if x == 1.
So the test is the same as:
if (x != 1)
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Best way to display decimal without trailing zeroes
...our examples have a max of 5).
If so, I would think that formatting with "0.#####" would do what you want.
static void Main(string[] args)
{
var dList = new decimal[] { 20, 20.00m, 20.5m, 20.5000m, 20.125m, 20.12500m, 0.000m };
foreach (var d in dList)
Console....
Naming returned columns in Pandas aggregate function? [duplicate]
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107
This will drop the outermost level from the hierarchical column index:
df = data.groupby(...)....
How can I obtain the element-wise logical NOT of a pandas Series?
...~s:
In [7]: s = pd.Series([True, True, False, True])
In [8]: ~s
Out[8]:
0 False
1 False
2 True
3 False
dtype: bool
Using Python2.7, NumPy 1.8.0, Pandas 0.13.1:
In [119]: s = pd.Series([True, True, False, True]*10000)
In [10]: %timeit np.invert(s)
10000 loops, best of 3: 91.8 µs...