Pandas is replacing rows with FALSE and TRUE with False and True
I think the output dataframe of read_csv already convert the columns to boolean values. You can verify it by calling df.info(). If you want to keep the columns as string values you need to pass a dict to the dtype parameter to specify it explicitly.
using pd.read_csv("my.csv"), I have certain rows that appear as either TRUE or FALSE. read_csv is changing these rows in the dataframe as "True" and "False".  Is there any way to keep case sensitivity when reading a CSV for true and false values?