I somehow missed Juan's reply.
Yes, I think Juan solved the problem.
Thanks, Juan!
On Sat, May 25, 2019 at 12:57 AM Robert Kern wrote:
> On Fri, May 24, 2019 at 9:33 PM C W wrote:
>
>> Thank you, Robert. I will take it up to the Pandas-dev mailing list.
>>
>> I&
ec):
return np.max(vec) - np.min(vec)
On Sat, May 25, 2019 at 12:06 AM Robert Kern wrote:
> On Fri, May 24, 2019 at 8:50 PM C W wrote:
>
>> I can't be the first person who asked about range() that calculates the
>> *actual* range of two numbers.
>>
>> I have
e
> on the scene, so it just made sense to adopt that name since it was the way
> to generate numbers in python.
>
> Ben
>
> On Fri, May 24, 2019 at 10:44 PM C W wrote:
>
>> When I looked up pandas mailing list. Numpy showed up. Maybe is because
>> Pandas is built
, 2019 at 10:34 PM Benjamin Root wrote:
> This is the numpy discussion list, not the pandas discussion list. Now,
> for numpy's part, I have had hankerings for a `np.minmax()` ufunc, but
> never enough to get over just calling min and max on my data separately.
>
> On Fri, May 24,
Hello all,
I am want to calculate the range of a vector. I saw that someone asked for
range() in 2011, but was it ever created?
https://github.com/pandas-dev/pandas/issues/288
Response at the time was to use df.describe(). But df.describe() gives all
the 5-number summary statistics, but I DON'T W
But, np.dot() gives me four axis shown below,
>>> z = np.dot(X, y.T)
>>> z.shape
(100, 28, 28, 1)
The fourth axis is unexpected. Should y.shape be (28, 28), not (1, 28, 28)?
Thanks again!
On Fri, Apr 19, 2019 at 6:39 PM Andras Deak wrote:
> On Sat, Apr 20, 2019 at 12:24 AM C W
Hello all,
Can an m x n x k matrix be multiplied with n x k matrix? Looking at the
Numpy doc page 46 (
https://docs.scipy.org/doc/numpy-1.11.0/numpy-user-1.11.0.pdf), it should
work.
It says the following:
A (3d array): 15 x 3 x 5
B (2d array): 3 x 5
Result (3d array): 15 x 3 x 5
But, th
frank here, just think about it.
On Fri, Feb 15, 2019 at 6:53 PM Daniele Nicolodi wrote:
> On 15-02-2019 14:48, C W wrote:
> > Fair enough. Python has been called the #1 language for data science. If
> > I'm slicing a[2:5] out of range, why not throw an error. This is>
>
Fair enough. Python has been called the #1 language for data science. If
I'm slicing a[2:5] out of range, why not throw an error. This is
disappointing!
I mean, why would you design a language to slice outside of range? Also, no
other language I know have this strange behavior.
On Fri, Feb 15, 20
86, 87, 86], name='a')
> b = pandas.Series([15, 72, 2, 3], name='b')
> result = a.subtract(b.shift()).dropna()
> print(result)
> 171.0
> 215.0
> 384.0
> dtype: float64
>
>
>
> On Wed, Feb 13, 2019 at 2:51 PM C W wrote:
>
>>
Dear list,
I have the following to Pandas Series: a, b. I want to slice and then
subtract. Like this: a[1:4] - b[0:3]. Why does it give me NaN? But it works
in Numpy.
Example 1: did not work
>>>a = pd.Series([85, 86, 87, 86])
>>>b = pd.Series([15, 72, 2, 3])
>>> a[1:4]-b[0:3] 0 NaN 1 14.0 2
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