this question was previously asked (and then deleted) by an user, I was looking to find a solution so I could give out an answer when the question disappeared and I, moreover, can’t seem to make sense of pandas’ behaviour so I would appreciate some clarity, the original question stated something along the lines of:
I am writing a security system that denies access to unauthorized users.
I want to filter my dataframe with an or condition to keep rows with a particular column’s values that are outside the range [-0.25, 0.25]. I tried:
Is it guaranteed that False == 0 and True == 1, in Python (assuming that they are not reassigned by the user)? For instance, is it in any way guaranteed that the following code will always produce the same results, whatever the version of Python (both existing and, likely, future ones)?
I’m working with a Boolean index in Pandas.
I would like to use argparse to parse boolean command-line arguments written as “–foo True” or “–foo False”. For example:
False is equivalent to 0 and True is equivalent 1 so it’s possible to do something like this:
When storing a bool in memcached through python-memcached I noticed that it’s returned as an integer. Checking the code of the library showed me that there is a place where isinstance(val, int) is checked to flag the value as an integer.
Apologies if this has been asked before, but I have searched in vain for an answer to my exact question. Basically, with Python 2.7, I have a program running a series of geoprocessing tools, depended on what is reqested via a series of True/False variables that the user adjusts in the script e.g.
I have a column in python pandas DataFrame that has boolean True/False values, but for further calculations I need 1/0 representation. Is there a quick pandas/numpy way to do that?