Data type of Dataframe column created using Faker

Question

df is a dataframe, created using the Faker library (used to generate datasets).

I want to assess df , storing the names of columns as string in one list; and their appropriate data types in a second list.

So far, I have:

columns = []
dtypes = []
for col_name, values in df.iteritems():
    columns.append(col_name)
    print(col_name)

I am stuck on the solution to detecting the data type of a given column. Could be stored as the data type class itself or as string literal.

Note: assessing the entire list df.column.values() is not necessary, as each instance/ record has to obey the same format Faker provides. Thus, assessing the very first column value suffices here.

Answer 1

My own proposed solution, using df.types as advised.

The crux of this being str(type(values[0]))[7:-1] , where I cast the class output as string and perform slicing of characters before and after my desired dtype (with single quotes kept).

columns = []
dtypes = []
for col_name, values in df.iteritems():
    columns.append(col_name)
    print(col_name)
    dtypes.append(type(values[0]))
    print(str(type(values[0]))[7:-1])