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Check image width and height before upload with Javascript
...file").change(function (e) {
var file, img;
if ((file = this.files[0])) {
img = new Image();
var objectUrl = _URL.createObjectURL(file);
img.onload = function () {
alert(this.width + " " + this.height);
_URL.revokeObjectURL(objectUrl);
...
How do I implement __getattribute__ without an infinite recursion error?
...ad, it works:
class D(object):
def __init__(self):
self.test=20
self.test2=21
def __getattribute__(self,name):
if name=='test':
return 0.
else:
return object.__getattribute__(self, name)
This works because object (in this example) is...
Get Substring between two characters using javascript
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edited Jun 3 '18 at 8:02
theUtherSide
2,58833 gold badges2727 silver badges3232 bronze badges
answer...
How do you represent a JSON array of strings?
...
303
I'll elaborate a bit more on ChrisR awesome answer and bring images from his awesome reference....
Get __name__ of calling function's module in Python
...ef info(msg):
frm = inspect.stack()[1]
mod = inspect.getmodule(frm[0])
print '[%s] %s' % (mod.__name__, msg)
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What is the most efficient way to create a dictionary of two pandas Dataframe columns?
...Speed comparion (using Wouter's method)
In [6]: df = pd.DataFrame(randint(0,10,10000).reshape(5000,2),columns=list('AB'))
In [7]: %timeit dict(zip(df.A,df.B))
1000 loops, best of 3: 1.27 ms per loop
In [8]: %timeit pd.Series(df.A.values,index=df.B).to_dict()
1000 loops, best of 3: 987 us per loop...
SQL Server: Maximum character length of object names
...m character length of object name (e.g. constraint, column) in SQL Server 2008?
3 Answers
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Replace only text inside a div using jquery
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edited Oct 29 '14 at 20:50
cuSK
7701010 silver badges2323 bronze badges
answered Aug 8 '12 at 14:56
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Difference between `mod` and `rem` in Haskell
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20
I had the same question about rem and mod in Clojure, and this was the answer.
– noahlz
Jul 11 '12 at...
Pandas aggregate count distinct
...
How about either of:
>>> df
date duration user_id
0 2013-04-01 30 0001
1 2013-04-01 15 0001
2 2013-04-01 20 0002
3 2013-04-02 15 0002
4 2013-04-02 30 0002
>>> df.groupby("date").agg({"duration": np.sum, "user_id...