Combining Huge H5 Files With Multiple Datasets Into One With Odo

I have a a number of large (13GB+ in size) h5 files, each h5 file has two datasets that were created with pandas: df.to_hdf('name_of_file_to_save', 'key_1',table=True) df.to_hdf(

Solution 1:

For this specific case it was a matter of having too many columns, which exceeded the memory limit allocated for that piece of information. The solution is to load the dataframe and transpose it.