title: How to run parsing logic of Pandas read_csv on custom data?
body: <p><a href="https://pandas.pydata.org/pandas-docs/version/0.23/generated/pandas.read_csv.html#pandas.read_csv" rel="nofollow noreferrer">read_csv</a> contains a lot of parsing logic to detect and convert CSV strings to numerical and datetime Pythong values. My question is, is there a way to call same conversions also on a DataFrame which contains columns with string data, but where the DataFrame is not stored in CSV file but comes from a different (unparsed) source? So only a memory DataFrame object is available.</p>
  
  <p>So saving such DataFrame to a CSV file and reading it back would do such conversion, but this looks very inefficient to me.</p>