Python "Value Error: cannot delete array elements" -- Why am I getting this?
I haven't been able to find anything about this value error online and I am at a complete loss as to why my code is eliciting this response.
I have a large dictionary of around 50 keys. The value associated with each key is a 2D array of many elements of the form [datetime object, some other info]
. A sample would look like this:
{'some_random_key': array([[dat开发者_运维问答etime(2010, 10, 26, 11, 5, 28, 157404), 14.1],
[datetime(2010, 10, 26, 11, 5, 38, 613066), 17.2]],
dtype=object),
'some_other_key': array([[datetime(2010, 10, 26, 11, 5, 28, 157404), 'true'],
[datetime(2010, 10, 26, 11, 5, 38, 613066), 'false']],
dtype=object)}
What I want my code to do is to allow a user to select a start and stop date and remove all of the array elements (for all of the keys) that are not within that range.
Placing print statements throughout the code I was able to deduce that it can find the dates that are out of range, but for some reason, the error occurs when it attempts to remove the element from the array.
Here is my code:
def selectDateRange(dictionary, start, stop):
#Make a clone dictionary to delete values from
theClone = dict(dictionary)
starting = datetime.strptime(start, '%d-%m-%Y') #put in datetime format
ending = datetime.strptime(stop+' '+ '23:59', '%d-%m-%Y %H:%M') #put in datetime format
#Get a list of all the keys in the dictionary
listOfKeys = theClone.keys()
#Go through each key in the list
for key in listOfKeys:
print key
#The value associate with each key is an array
innerAry = theClone[key]
#Loop through the array and . . .
for j, value in enumerate(reversed(innerAry)):
if (value[0] <= starting) or (value[0] >= ending):
#. . . delete anything that is not in the specified dateRange
del innerAry[j]
return theClone
This is the error message that I get:
ValueError: cannot delete array elements
and it occurs at the line: del innerAry[j]
Please help - perhaps you have the eye to see the problem where I cannot.
Thanks!
If you use numpy arrays, then use them as arrays and not as lists
numpy does comparison elementwise for the entire array, which can then be used to select the relevant subarray. This also removes the need for the inner loop.
>>> a = np.array([[datetime(2010, 10, 26, 11, 5, 28, 157404), 14.1],
[datetime(2010, 10, 26, 11, 5, 30, 613066), 17.2],
[datetime(2010, 10, 26, 11, 5, 31, 613066), 17.2],
[datetime(2010, 10, 26, 11, 5, 32, 613066), 17.2],
[datetime(2010, 10, 26, 11, 5, 33, 613066), 17.2],
[datetime(2010, 10, 26, 11, 5, 38, 613066), 17.2]],
dtype=object)
>>> start = datetime(2010, 10, 26, 11, 5, 28, 157405)
>>> end = datetime(2010, 10, 26, 11, 5, 33, 613066)
>>> (a[:,0] > start)&(a[:,0] < end)
array([False, True, True, True, False, False], dtype=bool)
>>> a[(a[:,0] > start)&(a[:,0] < end)]
array([[2010-10-26 11:05:30.613066, 17.2],
[2010-10-26 11:05:31.613066, 17.2],
[2010-10-26 11:05:32.613066, 17.2]], dtype=object)
just to make sure we still have datetimes in there:
>>> b = a[(a[:,0] > start)&(a[:,0] < end)]
>>> b[0,0]
datetime.datetime(2010, 10, 26, 11, 5, 30, 613066)
NumPy arrays are fixed in size. Use lists instead.
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