This question has been asked a couple of times already: Using numpy to build an array of all combinations of two arrays itertools product speed up The first link has a working numpy solution, that is claimed to be several times faster than itertools, though no benchmarks are provided. This code was written by a … Read more
This solution uses Kieth’s fromiter technique, but handles the two dimensional table structure of SQL results more intuitively. Also, it improves on Doug’s method by avoiding all the reshaping and flattening in python data types. Using a structured array we can read pretty much directly from the MySQL result into numpy, cutting out python data … Read more
I’ve seen this error before and it typically does have to do with pandas referencing an old version of numpy. But reinstalling may not help if your python path is still pointing to an old version of numpy. When you install numpy via pip, pip will tell you where it was installed. Something like pip … Read more
To test if an array equal to a is contained in the list my_list, use any((a == x).all() for x in my_list)
I encountered the same problem with VSCode, and I resolved it by adding the following path to the system environment. After that restart VSCode and everything is OK. C:\Users\<Your user name>\Anaconda3\Library\bin If the anaconda was not installed in the default directory, please find your own Anaconda3\Library\bin.
You can achieve this by creating a third array of dtype uint8, plus a bool array (which together are more memory efficient that one uint16 array). np.putmask is useful for avoiding a temp array. a = np.array([100, 200, 250], dtype=np.uint8) b = np.array([50, 50, 50], dtype=np.uint8) c = 255 – b # a temp uint8 … Read more
OP intended to start with empty array. So, here’s one approach using NumPy In [2]: a = np.empty((0,3), int) In [3]: a Out[3]: array([], shape=(0L, 3L), dtype=int32) In [4]: a = np.append(a, [[1,2,3]], axis=0) In [5]: a Out[5]: array([[1, 2, 3]]) In [6]: a = np.append(a, [[1,2,3]], axis=0) In [7]: a Out[7]: array([[1, 2, 3], … Read more
If X and beta do not have the same shape as the second term in the rhs of your last line (i.e. nsample), then you will get this type of error. To add an array to a tuple of arrays, they all must be the same shape. I would recommend looking at the numpy broadcasting … Read more
In order to bucket your series, you should use the pd.cut() function, like this: df[‘bin’] = pd.cut(df[‘1’], [0, 50, 100,200]) 0 1 file bin 0 person1 24 age.csv (0, 50] 1 person2 17 age.csv (0, 50] 2 person3 98 age.csv (50, 100] 3 person4 6 age.csv (0, 50] 4 person2 166 Height.csv (100, 200] 5 … Read more
If you’re sure that the value of img is None in your case, you can simply use if not img is None, or, equivalently, if img is not None. You don’t need to check the type explicitly. Note that None and False are not the same value. However, bool(None)==False, which is why if None fails. … Read more