大约有 47,000 项符合查询结果（耗时：0.0627秒） [XML]
How do I trim leading/trailing whitespace in a standard way?
...m leading space
while(isspace((unsigned char)*str)) str++;
if(*str == 0) // All spaces?
return str;
// Trim trailing space
end = str + strlen(str) - 1;
while(end > str && isspace((unsigned char)*end)) end--;
// Write new null terminator character
end[1] = '\0';
re...
How do I check if there are duplicates in a flat list?
...
406
Use set() to remove duplicates if all values are hashable:
>>> your_list = ['one', 't...
Are members of a C++ struct initialized to 0 by default?
... constructors
struct Snapshot {
int x;
double y;
Snapshot():x(0),y(0) { }
// other ctors / functions...
};
Will initialize both x and y to 0. Note that you can use x(), y() to initialize them disregarding of their type: That's then value initialization, and usually yields a proper...
If vs. Switch Speed
...
answered Jan 14 '09 at 23:16
Konrad RudolphKonrad Rudolph
461k118118 gold badges863863 silver badges11101110 bronze badges
...
Converting a column within pandas dataframe from int to string
...
In [16]: df = DataFrame(np.arange(10).reshape(5,2),columns=list('AB'))
In [17]: df
Out[17]:
A B
0 0 1
1 2 3
2 4 5
3 6 7
4 8 9
In [18]: df.dtypes
Out[18]:
A int64
B int64
dtype: object
Convert a series
In [19]: df['A'].apply(str)
Ou...
clearing a char array c
... to view this as a C/C++ null terminated string, setting the first byte to 0 will effectively clear the string.
share
|
improve this answer
|
follow
|
...
What is the difference between quiet NaN and signaling NaN?
...
70
When an operation results in a quiet NaN, there is no indication that anything is unusual until ...
Check if character is number?
...
70
You could use comparison operators to see if it is in the range of digit characters:
var c = ju...
Find nearest value in numpy array
...(array - value)).argmin()
return array[idx]
array = np.random.random(10)
print(array)
# [ 0.21069679 0.61290182 0.63425412 0.84635244 0.91599191 0.00213826
# 0.17104965 0.56874386 0.57319379 0.28719469]
value = 0.5
print(find_nearest(array, value))
# 0.568743859261
...