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How can I make pandas dataframe column headers all lowercase?
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How do you split a list into evenly sized chunks?
... yield lst[i:i + n]
import pprint
pprint.pprint(list(chunks(range(10, 75), 10)))
[[10, 11, 12, 13, 14, 15, 16, 17, 18, 19],
[20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
[30, 31, 32, 33, 34, 35, 36, 37, 38, 39],
[40, 41, 42, 43, 44, 45, 46, 47, 48, 49],
[50, 51, 52, 53, 54, 55, 56, 57, 58, 59],
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Disable/turn off inherited CSS3 transitions
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Get ffmpeg information in friendly way
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295
A bit late, but perhaps still relevant to someone..
ffprobe is indeed an excellent way to go. N...
How do I declare and initialize an array in Java?
...d(0, 100).toArray(); // From 0 to 100
int [] myIntArray = IntStream.of(12,25,36,85,28,96,47).toArray(); // The order is preserved.
int [] myIntArray = IntStream.of(12,25,36,85,28,96,47).sorted().toArray(); // Sort
For classes, for example String, it's the same:
String[] myStringArray = new Strin...
GLib compile error (ffi.h), but libffi is installed
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Python: Get the first character of the first string in a list?
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answered Aug 18 '11 at 13:25
agfagf
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How to create a video from images with FFmpeg?
... the fps video filter instead of -r for the output framerate
ffmpeg -r 1/5 -i img%03d.png -c:v libx264 -vf fps=25 -pix_fmt yuv420p out.mp4
Alternatively the format video filter can be added to the filter chain to replace -pix_fmt yuv420p like "fps=25,format=yuv420p". The advantage of this met...
Why is a round-trip conversion via a string not safe for a double?
...}
*dst = 0;
}
}
It turns out that _ecvt returns the string 845512408225570.
Notice the trailing zero? It turns out that makes all the difference!
When the zero is present, the result actually parses back to 0.84551240822557006, which is your original number -- so it compares equal, an...
Append a NumPy array to a NumPy array
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In [1]: import numpy as np
In [2]: a = np.array([[1, 2, 3], [4, 5, 6]])
In [3]: b = np.array([[9, 8, 7], [6, 5, 4]])
In [4]: np.concatenate((a, b))
Out[4]:
array([[1, 2, 3],
[4, 5, 6],
[9, 8, 7],
[6, 5, 4]])
or this:
In [1]: a = np.array([1, 2, 3])
In [2]: b = ...