Pandas Merge taking up too much resources

I am using the Solar Power Generation Dataset
I am trying to merge two csv files using pandas( and saving the output so it can be cached) but pandas is taking up too much RAM(>30 GB) and on save too much storage(~30 GB output csv). This is repeatable. The dataset files I am merging are the solar plant’s respective generation and weather data. It also takes a very long time to execute.
The initial files are all less than 6MB

Warning- this can only be done ideally with a local instance with ideally >64 GB RAM and >65GB free storage.


    temp1 = pd.read_csv(r"data/solar-power-generation/Plant_1_Generation_Data.csv")
    temp2 = pd.read_csv("data/solar-power-generation/Plant_1_Weather_Sensor_Data.csv").drop(columns=["SOURCE_KEY"])
    merged = pd.merge(temp1,temp2,on="PLANT_ID").drop(columns="PLANT_ID")

Thanks to anyone who responds!

Can you share the code that you are using for merging the Dataframes? Try merging a sample to make sure that the results are correct.

These might help you fix the issue:

Thank you for responding! I have posted the code.