Each DataFrame column must be exactly one type. For instance, every value in the column aspect_ratio is a 64-bit float, and every value in movie_facebook_likes is a 64-bit integer. Pandas defaults its core numeric types, integers, and floats to 64 bits regardless of the size necessary for all data to fit in memory. Even if a column consists entirely of the integer value 0, the data type will still be int64. get_dtype_counts is a convenience method for directly returning the count of all the data types in the DataFrame.

The object data type is the one data type that is unlike the others. A column that is of object data type may contain values that are of any valid Python object. Typically, when a column is of the object data type, it signals that the entire column is strings. This isn't necessarily the case as it is possible for these columns to contain a mixture of integers, booleans, strings, or other, even more complex Python objects such as lists or dictionaries. The object data type is a catch-all for columns that pandas doesn’t recognize as any other specific type.