, , , , , , , series also has to_csv methodin [ ]dates pd date_range(''periods= in [ ]ts series(np arange( )index=datesin [ ]ts to_csv('ch /tseries csv'in [ ]!cat ch /tseries csv : : , : : , : : , : : , : : , : : , : : , with bit of wrangling (no headerfirst column as index)you can read csv version of series with read_csvbut there is also from_csv convenience method that makes it bit simplerin [ ]series from_csv('ch /tseries csv'parse_dates=trueout[ ] see the docstrings for to_csv and from_csv in ipython for more information manually working with delimited formats most forms of tabular data can be loaded from disk using functions like pan das read_table in some caseshoweversome manual processing may be necessary it' not uncommon to receive file with one or more malformed lines that trip up read_table to illustrate the basic toolsconsider small csv filein [ ]!cat ch /ex csv " "," "," " "," "," " "," "," "," for any file with single-character delimiteryou can use python' built-in csv module to use itpass any open file or file-like object to csv readerreading and writing data in text format www it-ebooks info