大约有 41,200 项符合查询结果（耗时：0.0225秒） [XML]
How to deal with SettingWithCopyWarning in Pandas?
I just upgraded my Pandas from 0.11 to 0.13.0rc1. Now, the application is popping out many new warnings. One of them like this:
...
NameError: global name 'unicode' is not defined - in Python 3
...
Python 3 renamed the unicode type to str, the old str type has been replaced by bytes.
if isinstance(unicode_or_str, str):
text = unicode_or_str
decoded = False
else:
text = unicode_or_str.decode(encoding)
decoded =...
map function for objects (instead of arrays)
...
38 Answers
38
Active
...
Reorder levels of a factor without changing order of values
...f <- data.frame(f = 1:4, g = letters[1:4])
df
# f g
# 1 1 a
# 2 2 b
# 3 3 c
# 4 4 d
levels(df$g)
# [1] "a" "b" "c" "d"
df$g <- factor(df$g, levels = letters[4:1])
# levels(df$g)
# [1] "d" "c" "b" "a"
df
# f g
# 1 1 a
# 2 2 b
# 3 3 c
# 4 4 d
...
Modulo operator with negative values [duplicate]
...
3 Answers
3
Active
...
How to do multiple arguments to map function where one remains the same in python?
...
One option is a list comprehension:
[add(x, 2) for x in [1, 2, 3]]
More options:
a = [1, 2, 3]
import functools
map(functools.partial(add, y=2), a)
import itertools
map(add, a, itertools.repeat(2, len(a)))
...
Get a random boolean in python?
...
349
Adam's answer is quite fast, but I found that random.getrandbits(1) to be quite a lot faster. ...
How to check if variable is string with python 2 and 3 compatibility
I'm aware that I can use: isinstance(x, str) in python-3.x but I need to check if something is a string in python-2.x as well. Will isinstance(x, str) work as expected in python-2.x? Or will I need to check the version and use isinstance(x, basestr) ?
...
How do I detect the Python version at runtime? [duplicate]
I have a Python file which might have to support Python versions < 3.x and >= 3.x. Is there a way to introspect the Python runtime to know the version which it is running (for example, 2.6 or 3.2.x )?
...
Detect and exclude outliers in Pandas data frame
...ression would do that in one shot.
df = pd.DataFrame(np.random.randn(100, 3))
from scipy import stats
df[(np.abs(stats.zscore(df)) < 3).all(axis=1)]
description:
For each column, first it computes the Z-score of each value in the
column, relative to the column mean and standard deviation.
...