On the other hand, I recommend that you have a look at ROOT's RDataFrame and its feature to convert to pandas:
https://root.cern/doc/master/df026__AsNumpyArrays_8py.html
You can process the dataset in your ROOT file with RDataFrame (filter it, define new columns, etc.) and then convert the columns you are interested in into Numpy arrays, which can be fed to pandas to create a dataframe. The good thing about this approach is that RDataFrame will not load all the dataset in memory to process it, so you will likely not experience the memory error issue.