I need to do this while keeping the group by index of the grouped by Column as the index. I can’t use reset_index etc. there are multiple columns I need to keep. I only want to call an agh function on one column, grouped by another, while keeping all the other columns with their values unaffected by agg and attached to their original row in the aggregated column. The agg function I’m using is max so it is a specific row.

I have a list of dicts where each dict can have different keys. I want to create a dataframe with one row where each key is a column and the row is its value:

I have a Pandas dataframe with two columns with the same name and I want to rename one of them. I know the index of each one but I haven’t found a way to rename a column by index, and all the ways I have found involve to get the name of the column based on the index which wouldn’t work for me since that would return two indexes.

I’m trying to merge two CSVs containing gene names, the first one with 6736 gene names and the second with 10745 gene names. I am using the pandas merge function to merge the CSVs but the resulting list only has 6665 gene names when it should have 6736. Why is pandas dropping certain rows?

How to change the line spacing of all tables displayed by Pandas? I.e. to do the same thing that this code does, but globally.

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import boto3

I have a table like the following