  Type inference refers to the task of inferring the data type of a given
column of data. Current approaches often fail when data contains missing data
and anomalies, which are found commonly in real-world data sets. In this paper,
we propose ptype, a probabilistic robust type inference method that allows us
to detect such entries, and infer data types. We further show that the proposed
method outperforms the existing methods.
