. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 10.5 Dispatching to instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 10.6 Flexible . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 13.3 Time series-related instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 13.4 Up- and downsampling sort_index (GH92, PR362) • Added fast get_value and put_value methods to DataFrame (GH360) • Added cov instance methods to Series and DataFrame (GH194, PR362) • Added kind=’bar’ option to DataFrame.plot (PR348)

passes the combiner function pairs of Series (i.e., columns whose names are the same). So, for instance, to reproduce combine_first() as above: 3.3. Essential basic functionality 49 pandas: powerful datetime64[ns] You may also pass additional arguments and keyword arguments to the apply() method. For instance, consider the following function you would like to apply: def subtract_and_divide(x, sub, divide=1): which returns namedtuples of the values and which is generally much faster than iterrows(). For instance, a contrived way to transpose the DataFrame would be: In [258]: df2 = pd.DataFrame({'x': [1, 2

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 364 13.6 Dispatching to instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366 13.7 Flexible . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 424 16.6 Time series-related instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 433 16.7 Up- and downsampling name or sql query). In practice, you have to provide a SQLAlchemy engine to the sql functions. To connect with SQLAlchemy you use the create_engine() function to create an engine object from database URI

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 533 17.7 Dispatching to instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 534 17.8 Flexible . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 602 iv 20.7 Time series-related instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 614 20.8 Resampling now accept multiplied freq. Also, Period.freq and PeriodIndex.freq are now stored as a DateOffset instance like DatetimeIndex, and not as str (GH7811) A multiplied freq represents a span of corresponding

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 449 16.7 Dispatching to instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 450 16.8 Flexible . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512 19.6 Time series-related instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 521 19.7 Up- and downsampling data for the next expiry after the given date is returned. Option data frames are now saved on the instance as callsYYMMDD or putsYYMMDD. Previously they were saved as callsMMYY and putsMMYY. The next expiry

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 438 16.6 Dispatching to instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 440 16.7 Flexible . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 502 19.6 Time series-related instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 511 19.7 Up- and downsampling data for the next expiry after the given date is returned. Option data frames are now saved on the instance as callsYYMMDD or putsYYMMDD. Previously they were saved as callsMMYY and putsMMYY. The next expiry

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 741 16.7 Dispatching to instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 743 16.8 Flexible . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 840 19.9 Time series-related instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 842 19.9.1 Shifting 15 Other API Changes • Timestamp.to_pydatetime will issue a UserWarning when warn=True, and the instance has a non- zero number of nanoseconds, previously this would print a message to stdout (GH14101)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 739 16.7 Dispatching to instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 741 16.8 Flexible . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 836 19.9 Time series-related instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 839 19.9.1 Shifting 15 Other API Changes • Timestamp.to_pydatetime will issue a UserWarning when warn=True, and the instance has a non- zero number of nanoseconds, previously this would print a message to stdout (GH14101)

common SQL operation would be getting the count of records in each group throughout a dataset. For instance, a query getting us the number of tips left by sex: SELECT sex, count(*) FROM tips GROUP BY sex; 87 Male 157 Name: total_bill, dtype: int64 Multiple functions can also be applied at once. For instance, say we’d like to see how tip amount differs by day of the week - agg() allows you to pass a dictionary passes the combiner function pairs of Series (i.e., columns whose names are the same). So, for instance, to reproduce combine_first() as above: In [76]: def combiner(x, y): ....: return np.where(pd

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 662 17.7 Dispatching to instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 664 17.8 Flexible . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 752 20.8 Time series-related instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 754 20.8.1 Shifting dtype('int64') Other API Changes • Timestamp.to_pydatetime will issue a UserWarning when warn=True, and the instance has a non- zero number of nanoseconds, previously this would print a message to stdout (GH14101)