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Extract traceback info from an exception object
...to this question depends on the version of Python you're using.
In Python 3
It's simple: exceptions come equipped with a __traceback__ attribute that contains the traceback. This attribute is also writable, and can be conveniently set using the with_traceback method of exceptions:
raise Exceptio...
What does the slash mean in help() output?
What does the / mean in Python 3.4's help output for range before the closing parenthesis?
3 Answers
...
pandas DataFrame: replace nan values with average of columns
...
283
You can simply use DataFrame.fillna to fill the nan's directly:
In [27]: df
Out[27]:
...
How to find out what type of a Mat object is with Mat::type() in OpenCV
...e CV_16U: r = "16U"; break;
case CV_16S: r = "16S"; break;
case CV_32S: r = "32S"; break;
case CV_32F: r = "32F"; break;
case CV_64F: r = "64F"; break;
default: r = "User"; break;
}
r += "C";
r += (chans+'0');
return r;
}
If M is a var of type Mat you can call it ...
How to use glob() to find files recursively?
...lib.Path.rglob from the the pathlib module, which was introduced in Python 3.5.
from pathlib import Path
for path in Path('src').rglob('*.c'):
print(path.name)
If you don't want to use pathlib, use can use glob.glob('**/*.c'), but don't forget to pass in the recursive keyword parameter and it ...
What's the difference between VARCHAR and CHAR?
...
372
VARCHAR is variable-length.
CHAR is fixed length.
If your content is a fixed size, you'll ge...
How do I loop through a list by twos? [duplicate]
...
392
You can use for in range with a step size of 2:
Python 2
for i in xrange(0,10,2):
print(i)...
how to convert array values from string to int?
...
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edited Apr 23 '19 at 10:46
Rahul
16.8k77 gold badges3434 silver badges5353 bronze badges
a...
Create Pandas DataFrame from a string
...
538
A simple way to do this is to use StringIO.StringIO (python2) or io.StringIO (python3) and pass...
Group by multiple columns in dplyr, using string vector input
...e so:
data = data.frame(
asihckhdoydkhxiydfgfTgdsx = sample(LETTERS[1:3], 100, replace=TRUE),
a30mvxigxkghc5cdsvxvyv0ja = sample(LETTERS[1:3], 100, replace=TRUE),
value = rnorm(100)
)
# get the columns we want to average within
columns = names(data)[-3]
library(dplyr)
df1 <- data %...