I am trying to clean my dataframe such that if my "Base_2007" and "Base_2011" column contains NA, then I should completely drop that county. In my case since both Counties contains NA both of them will be dropped. Thus empty dataset will be returned. Is it possible to do something...
New to Python here.I am looking for a simple way of creating a list (Output), which returns the count of the elements of another objective list (MyList) while preserving the indexing(?).
I am trying to perform a groupby filter that is very similar to the example in this documentation: pandas groupby filter
I have a data-frame like I want to filter them in a priority like this: If colC == E then return E, after that check colB == D return D otherwise return colA The output is
How do I select only True values?What I have tried:This includes "c" while I need to return a list of a, b and d
This is a self-answered QnA meant to instruct users about the pitfalls and benefits of apply. I have seen many answers posted to questions on Stack Overflow involving the use of apply. I have also seen users commenting under them saying that "apply is slow", and should be avoided".
Given the dataif I try constructing a dataframe like thisit works fine. However, this(which I would expect to be equivalent) fails with the weird error: KeyError: 'x'. What's wrong?
I would like to fill df's nan with an average of adjacent elements.Consider a dataframe:My desired output is:
I have two lists like so:How do I combine the lists into one set of tuples for a pandas dataframe?like so:
Below is a subset of a pandas dataframe I have and I am trying to remove multiple rows based on some conditions.