Using an index to get an item
I have a list in python (‘A’,’B’,’C’,’D’,’E’), how do I get which item is under a particular index number?
Python
How can I use numpy.correlate to do autocorrelation?
I need to do auto-correlation of a set of numbers, which as I understand it is just the correlation of the set with itself.
How to use python-docx to replace text in a Word document and save
The oodocx module mentioned in the same page refers the user to an /examples folder that does not seem to be there.
I have read the documentation of python-docx 0.7.2, plus everything I could find in Stackoverflow on the subject, so please believe that I have done my “homework”.
Scale matplotlib.pyplot.Axes.scatter markersize by x-scale
I would like to scale the markersize of matplotlib.pyplot.Axes.scatter plot based on the number of points on the x/y-axis.
How to delete Tkinter widgets from a window?
I have a list of tkinter widgets that I want to change dynamically.
Pandas Groupby and Sum Only One Column
So I have a dataframe, df1, that looks like the following:
OpenCV: Choosing HSV thresholds for color filtering
In order to filter a color out of an image, it’s necessary to set boundaries as to which color needs to be detected. I have a feeling this is mostly a trial-and-error process. Are there any ways to quickly find the correct thresholds for a particular color? In this specific case I’m trying to detect the gray area of the graph in the picture below. This without detecting the dotted lines of course. For this example I need very specific boundaries. The question is, how can I find them easily?
Slicing a list into n nearly-equal-length partitions
I’m looking for a fast, clean, pythonic way to divide a list into exactly n nearly-equal partitions. partition([1,2,3,4,5],5)->[[1],[2],[3],[4],[5]] partition([1,2,3,4,5],2)->[[1,2],[3,4,5]] (or [[1,2,3],[4,5]]) partition([1,2,3,4,5],3)->[[1,2],[3,4],[5]] (there are other ways to slice this one too) There are several answers in here Iteration over list slices that run very close to what I want, except they are focused on the … Read more
extracting days from a numpy.timedelta64 value
I am using pandas/python and I have two date time series s1 and s2, that have been generated using the ‘to_datetime’ function on a field of the df containing dates/times.
LogisticRegression: Unknown label type: ‘continuous’ using sklearn in python
I have the following code to test some of most popular ML algorithms of sklearn python library: