大约有 37,000 项符合查询结果（耗时：0.0527秒） [XML]
JavaScript is in array
...a RBala R
99.2k2222 gold badges178178 silver badges201201 bronze badges
25
...
Reduce left and right margins in matplotlib plot
...E.g.
import matplotlib.pyplot as plt
import numpy as np
data = np.arange(3000).reshape((100,30))
plt.imshow(data)
plt.savefig('test.png', bbox_inches='tight')
Another way is to use fig.tight_layout()
import matplotlib.pyplot as plt
import numpy as np
xs = np.linspace(0, 1, 20); ys = np.sin(xs)
...
How do I scale a stubborn SVG embedded with the tag?
...dd the following attributes:
preserveAspectRatio="xMinYMin meet"
viewBox="0 0 {width} {height}"
Replace {width} and {height} with some defaults for the viewBox. I used the values from the "width" and "height" attributes of the SVG tag and it seemed to work.
Save the SVG and it should now scale a...
Divide a number by 3 without using *, /, +, -, % operators
... x = t;
}
return y;
}
int divideby3(int num)
{
int sum = 0;
while (num > 3) {
sum = add(num >> 2, sum);
num = add(num >> 2, num & 3);
}
if (num == 3)
sum = add(sum, 1);
return sum;
}
As Jim commented this works, because:...
add a string prefix to each value in a string column using Pandas
...['col'].astype(str)
Example:
>>> df = pd.DataFrame({'col':['a',0]})
>>> df
col
0 a
1 0
>>> df['col'] = 'str' + df['col'].astype(str)
>>> df
col
0 stra
1 str0
share
...
Converting JSON String to Dictionary Not List
...with a dictionary inside. You can access your dictionary by accessing item 0 in the list, as shown below:
json1_data = json.loads(json1_str)[0]
Now you can access the data stored in datapoints just as you were expecting:
datapoints = json1_data['datapoints']
I have one more question if an...
How to sort a dataFrame in python pandas by two or more columns?
...
490
As of the 0.17.0 release, the sort method was deprecated in favor of sort_values. sort was comp...
Too many 'if' statements?
...
600
If you cannot come up with a formula, you can use a table for such a limited number of outcomes...
Regular expression to match non-ASCII characters?
...
This should do it:
[^\x00-\x7F]+
It matches any character which is not contained in the ASCII character set (0-127, i.e. 0x0 to 0x7F).
You can do the same thing with Unicode:
[^\u0000-\u007F]+
For unicode you can look at this 2 resources:
...
How to load a tsv file into a Pandas DataFrame?
...
Note: As of 17.0 from_csv is discouraged: use pd.read_csv instead
The documentation lists a .from_csv function that appears to do what you want:
DataFrame.from_csv('c:/~/trainSetRel3.txt', sep='\t')
If you have a header, you can pass he...