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How to convert index of a pandas dataframe into a column?
...either:
df['index1'] = df.index
or, .reset_index:
df.reset_index(level=0, inplace=True)
so, if you have a multi-index frame with 3 levels of index, like:
>>> df
val
tick tag obs
2016-02-26 C 2 0.0139
2016-02-27 A 2 0.5577
2016-02-28 C ...
How to convert an integer to a string in any base?
...tring.digits + string.ascii_letters
def int2base(x, base):
if x < 0:
sign = -1
elif x == 0:
return digs[0]
else:
sign = 1
x *= sign
digits = []
while x:
digits.append(digs[int(x % base)])
x = int(x / base)
if sign < 0:
...
How to remove an element slowly with jQuery?
...
answered Nov 27 '09 at 7:09
GregGreg
7,18077 gold badges3939 silver badges6464 bronze badges
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How do I get Flask to run on port 80?
I have a Flask server running through port 5000, and it's fine. I can access it at http://example.com:5000
14 Answers
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Common MySQL fields and their appropriate data types
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answered Dec 10 '08 at 0:57
da5idda5id
8,83288 gold badges3636 silver badges5050 bronze badges
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How to split a delimited string into an array in awk?
...
Have you tried:
echo "12|23|11" | awk '{split($0,a,"|"); print a[3],a[2],a[1]}'
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How can I scale an image in a CSS sprite
... not all http://caniuse.com/#search=background-size)
background-size : 150% 150%;
Or
You can use a combo of zoom for webkit/ie and transform:scale for Firefox(-moz-) and Opera(-o-) for cross-browser desktop & mobile
[class^="icon-"]{
display: inline-block;
background: url('../img/...
PHP cURL vs file_get_contents
...
answered Jun 16 '12 at 16:00
XeoncrossXeoncross
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Parse (split) a string in C++ using string delimiter (standard C++)
...>=tiger";
std::string delimiter = ">=";
std::string token = s.substr(0, s.find(delimiter)); // token is "scott"
The find(const string& str, size_t pos = 0) function returns the position of the first occurrence of str in the string, or npos if the string is not found.
The substr(size_t p...
binning data in python with scipy/numpy
... easier to use numpy.digitize():
import numpy
data = numpy.random.random(100)
bins = numpy.linspace(0, 1, 10)
digitized = numpy.digitize(data, bins)
bin_means = [data[digitized == i].mean() for i in range(1, len(bins))]
An alternative to this is to use numpy.histogram():
bin_means = (numpy.histo...