I had luck by reading the entire file in as a string, then manually specifying datatypes later. In my situation, I had a column which had IDs that could contain strings like "08" which would be different from an ID of "8".

The first thing I tried was df = pd.read_csv(dtype={"ID": str}) but for some reason, this was still converting "08" to "8" (at least it was still a string, but it must have been interpreted as an integer first, which removed the leading 0).

The thing that worked for me was this: df = pd.read_csv(dtype=str) And then I could go through and manually assign other columns their datatypes as needed like @lbolla mentioned.

For some reason, applying the data type across the entire document skipped the type inference step I suppose. Annoying this isn't the default behavior when specifying a specific column data type :(