Specifying data type in Pandas csv reader

Question

I am just getting started with Pandas and I am reading in a csv file using the read_csv() method. The difficulty I am having is preventing pandas from converting my telephone numbers to large numbers, instead of keeping them as strings. I defined a converter which just left the numbers alone, but then they still converted to numbers. When I changed my converter to prepend a 'z' to the phone numbers, then they stayed strings. Is there some way to keep them strings without modifying the values of the fields?

Answer 1

Since Pandas 0.11.0 you can use dtype argument to explicitly specify data type for each column:

d = pandas.read_csv('foo.csv', dtype={'BAR': 'S10'}) 

Answer 2

It looks like you can't avoid pandas from trying to convert numeric/boolean values in the CSV file. Take a look at the source code of pandas for the IO parsers, in particular functions _convert_to_ndarrays, and _convert_types. https://github.com/pydata/pandas/blob/master/pandas/io/parsers.py

You can always assign the type you want after you have read the file:

df.phone = df.phone.astype(str)