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Creating password requirements for a user in Django using:
django.contrib.auth.password_validation.UserAttributeSimilarityValidator django.contrib.auth.password_validation.MinimumLengthValidator django.contrib.auth.password_validation.CommonPasswordValidator django.contrib.auth.password_validation.NumericPasswordValidator
However, when I use the password $a1ABCD%#@ it gives me the error message:
At least one special character (punctuation, brackets, quotes, etc.), at least one lowercase character, at least one uppercase character, at least one digit, at least 8 chars.
$a1ABCD@ seems to work though. Any ideas?
In the training process, I want to change the parameters of neural network from a small scale network.
For example, the filter of smale scale network is 3~3, the training neural network is 9~9. I want the filter value of the training neural network come from the the filter of smale scale network.
I use "tf.trainable_variables(scope='CNN')" and "tf.tile" to expand the dimension, and then "tf.assign" is used to achieve this target. However, it can apply in the change of single value.
How can I change the all values in the same order:sess.run()? Because the network has many different dimension of filters.
I am trying to merge 2 csv files by column.
my both csv file has a format as such and they both ends with '_4.csv' as filename:
0-10 ,83.72,66.76,86.98 11-20 ,15.01,31.12,12.04 21-30 ,1.14,2.05,0.94 31-40 ,0.13,0.07,0.03 41-50 ,0.0,0.0,0.0 51-60 ,0.0,0.0,0.0 over 60 ,0.0,0.0,0.0 UHF case ,0.0,0.0,0.0
#combine 2 csv into 1 by columns files_in_dir = [f for f in os.listdir(os.getcwd()) if f.endswith('_4.csv')] temp_data =  for filenames in files_in_dir: temp_data.append(np.loadtxt(filenames,dtype='str')) temp_data = np.array(temp_data) np.savetxt('_mix.csv',temp_data.transpose(),fmt='%s',delimiter=',')
however the error said:
temp_data.append(np.loadtxt(filenames,dtype='str')) for x in read_data(_loadtxt_chunksize): raise ValueError("Wrong number of columns at line %d" ValueError: Wrong number of columns at line 2
not sure if it is related to the first column being strings rather than values.
Does anyone know how to fix it? much appreciation
I have a simple df:
a = pd.DataFrame([[1,2,3,5,8],['jack','jeff',np.nan,np.nan,'tesla']]) a.index = [['number','name']] a=a.T
and it looks like this:
number name 0 1 jack 1 2 jeff 2 3 NaN 3 5 NaN 4 8 tesla
When I am tring to do a .loc like
a.loc[a['number']==5], I got this type error:
Traceback (most recent call last): File "c:\Users\Administrator\Documents\proj\test.py", line 13, in <module> a.loc[a['number']==5] File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\frame.py", line 2878, in __getitem__ return self._get_item_cache(key) File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\generic.py", line 3541, in _get_item_cache values = self._mgr.iget(loc) File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 988, in iget block = self.blocks[self.blknos[i]] TypeError: only integer scalar arrays can be converted to a scalar index
I searched this error and tried some solutions like using
a.loc[np.array(a)['number']==5] or reinstall pandas and numpy or anaconda but they are not working.
My pandas version is 1.3 and numpy version is 1.19.2
I am trying to plot the energy consumption profile of an electric vehicle. I am using the elevation profile vs the horizontal distance the vehicle runs along a path. I want to add a second x-axis on top of the plot to represent by each chunk of distance, what the energy consumption value was at that precise location. This is what I have so far, but it's not precisely what I need: ELevation profile plot. I know this should be fairly simple as it is only adding a second x-axis that matches with the primary x-axis, but I have wasted an entire day trying to figure out unsuccessfully :( Any insights will be greatly appreciated. Thanks in advance!