I’m fairly new to numpy and pandas, let’s say that I have a 2D numpy array and I need to delete all rows in which the second value contain only the letters ‘A’, ‘C’, ‘T’, ‘G’ and ‘N’ so after filtering I can get this I wanted to do 3 for loops that are checking each char one by one
When spawn processes, Does Lock have different id?
I’m trying to figure out how Lock works under the hood. I run this code on MacOS which using “spawn” as default method to start new process. Output: The Lock works in my code. However, the ids of lock make me confused. Since idare different, are they still same one lock or there are multiple locks and they somehow communicate
How to set non-adjacent cell range for XlsxWriter Data Validation
I am using the Python XlsxWriter module to add a drop down list using the method data_validation currently I have the set up so I drop duplicates on a Pandas Series and convert that into a list and set the values for the drop down list like so: This works fine however if the list exceeds 255 characters as according
Fast shaping of multiprocessing return values in Python
I have a function with list valued return values that I’m multiprocessing in Python and I need to concatenate them to 1D lists at the end. The following is a sample code for demonstration: The output for illustration is: The problem is that the list L that I’m processing is pretty huge and that the concatenations at the end take
Performance comparison: Why is it faster to copy an entire numpy Matrix and then change one column than to just use numpy.column_stack?
I am trying to improve the performance of some Python code. In that code, one column of a matrix (numpy-array) has to be changed temporarily. The given code looks as follows: Now I thought it should be a big improvement to not create a copy of the entire matrix A (in the example used, the matrix is 500×500 with all
How to subtract baseline from spectrum with rising tail in python?
I have a spectrum that I want to subtract a baseline from. The spectrum data are: I’ve taken only every 20th data point from the actual data file, but the general shape is preserved. Original_spectrum There is a clear tail in around the high x values. Assume the tail is an artifact and needs to be removed. I’ve tried solutions
Do Machine Learning Algorithms read data top-down or bottom up?
I’m new to Machine Learning and I’m a bit confused about how data is being read for the training/testing process. Assuming my data works with date and I want the model to read the later dates first before getting to the newer dates, the data is saved in the form of earliest date on line 1 and line n has
‘ManyToManyDescriptor’ object has no attribute ‘all’ when accessing related_name
I have 3 models: and I am trying to access all passengers of a certain Flight when I visit /<int:flight_id> like this: Your response is appreciated Thank you In advanced Answer You can access passengers of an instance of Flight, not directly from class Flight:
Am I using the on_guild_leave function correctly?
So I looked at many sources saying that on_guild_leave is how it is used, but I can’t get it to work. Here is my code: Can anyone seem to help? on_guild_join works, but on_guild_leave doesn’t. Answer on_guild_leave doesn’t exist, use on_guild_remove instead. Docs for on_guild_remove
python, How to get smoother value?
Somehow seaborn draws smoother line than actual data. For example, for x-value 0.18, actual data is like 11 but value on smoother line is about 3. How would I get value 3 for the x-value when given the list of data? The actual data are: Answer You can access the plot data with: out: