I have 2 dataframes:

One column in my Pandas dataframe is too long. How can I set max row height (not number of rows in a dataframe) in pandas so that I can truncate the cells with too much content and have a balanced view of all columns?

Given a pandas DataFrame with several columns containing potentially missing values(NaN).
The goal is to efficiently find the first non-null value for each row.
A similar Question using polars Dataframe and solution is here :/q/77401947/6037956

Just upgraded numpy to the latest intel conda’s, I am at pandas 2.2.1, numpy 1.24.3 and numexpr 2.10.0

Just upgraded numpy to the latest intel conda’s, I am at pandas 2.2.1, numpy 1.24.3 and numexpr 2.10.0

Can somebody explain the following behavior?

For some reason df.replace() is not working for me. I want to fill nan values with a dummy value, pivot, then turn the dummy values back into nans using replace, but replace is not working. On further investigation it seems that the ‘yy’ value is not being recognised as the same as the fillna value so the function cant find anything to replace. e.g.

I’m not sure why but after getting a new install of windows and a new pycharm install and trying to run some previously functional code I am now getting the above error with the code below. Is it a setup issue or has something changed that now makes this code not function? Error happens on the last line. The error doesn’t make sense to me as there should be no conversion required for ndarray to ndarray.

I have the following dataframe

I’m dealing with a large data set and I have a column that is treat as an object