Le 27/04/2020 à 04:46, Bob van der Poel a écrit :
Does this make as much sense as anything else? I need to track calls to a
function to make sure it doesn't get called to too great a depth. I had a
global which I inc/dec and then check in the function. Works fine, but I do
need to keep a global a
Hello
It's not clear to me what the differences between
Axes and AxesSubplot classes are
AxesSubplot is a sub class of Axes
It is possible to draw in objects of both type with
plot, scatter ...
Axes object seems to be able to be inserted in AxesSubplot object
(It is strange because AxesSubplot
bvdp於 2020年4月28日星期二 UTC+8上午9時46分35秒寫道：
> Oh my, that is very cool! So, I can do this:
>
> def foo(i):
> if not 'bar' in foo.__dict__:
> foo.bar = 5
> foo.bar += i
You can have function attribute created this way if you like:
def foo(i):
foo.bar += i
foo.bar = 5
-
Oh my, that is very cool! So, I can do this:
def foo(i):
if not 'bar' in foo.__dict__:
foo.bar = 5
foo.bar += i
for a in range(10):
foo(1)
print (foo.bar)
Thanks. I will have to play more with this.
On Mon, Apr 27, 2020 at 5:31 PM Michael Torrie wrote:
> On 4/27/20 1
On 4/27/20 10:39 AM, Bob van der Poel wrote:
> Thanks Chris!
>
> At least my code isn't (quite!) as bad as the xkcd example :)
>
> Guess my "concern" is using the initialized array in the function:
>
>def myfunct(a, b, c=array[0,1,2,3] )
>
> always feels like an abuse.
>
> Has anyone serio
1: Does the code run to completion without errors?
If there's an exception then the data may not get to the file because
I/O is normally buffered in memory and written out in larger chunks
as the buffer fills i.e. at a time later than your .writerow() call.
2: If you delete the CSV file
Thanks Chris!
At least my code isn't (quite!) as bad as the xkcd example :)
Guess my "concern" is using the initialized array in the function:
def myfunct(a, b, c=array[0,1,2,3] )
always feels like an abuse.
Has anyone seriously considered implementing a true static variable in a
function?
FOLLWOING IS MY CODE
import pandas as pd
import csv
from sklearn.preprocessing import LabelEncoder
from sklearn.feature_selection import chi2
with open("D:\PHD\obranking\\test_chi.csv", 'w') as csvfilew1:
fields = ['index', 'feature name', 'p_value']
csvwriter1 = csv.DictWriter(csvfilew1, f
PS C:\Users\amanb\OneDrive\Desktop\jarvis> pip install pyttsx3
Collecting pyttsx3
Using cached pyttsx3-2.87-py3-none-any.whl (39 kB)
Collecting comtypes; platform_system == "Windows"
Using cached comtypes-1.1.7.zip (180 kB)
Installing collected packages: comtypes, pyttsx3
Running setup.py i
Hi i am trying to use chi-square Test to select most important columns among
5501 columns. But for most of the columns i am getting NAN value as a Chi test
value
import pandas as pd
from sklearn.preprocessing import LabelEncoder
from sklearn.feature_selection import chi2
cols =[]
cols.append(int
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