203918 0.11 third 1 0.113613 0.33 • drop_duplicates and duplicated now accept a keep keyword to target first, last, and all duplicates. 1.1. v0.17.0 (October 9, 2015) 13 pandas: powerful Python data can now accept errors keyword to suppress ValueError raised when any of label does not exist in the target data. (GH6736) In [43]: df = DataFrame(np.random.randn(3, 3), columns=['A', 'B', 'C']) In [44]: Release 0.17.0 • Index.get_indexer now supports method=’pad’ and method=’backfill’ even for any target ar- ray, not just monotonic targets. These methods also work for monotonic decreasing as well as

DataFrame.rename() and DataFrame.reindex() methods have gained the axis keyword to specify the axis to target with the operation (GH12392). Here’s rename: In [11]: df = pd.DataFrame({"A": [1, 2, 3], "B": [4 following expression, you would get a not very helpful error message: In [3]: pd.eval("a = 1 + 2", target=arr, inplace=True) ... IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) the error message is now this: In [3]: pd.eval("a = 1 + 2", target=arr, inplace=True) ... ValueError: Cannot assign expression output to target It also used to be possible to evaluate expressions inplace

875457 0.51 third 1.0 0.585937 0.62 • drop_duplicates and duplicated now accept a keep keyword to target first, last, and all duplicates. The take_last keyword is deprecated, see here (GH6511, GH8505) can now accept errors keyword to suppress ValueError raised when any of label does not exist in the target data. (GH6736) In [43]: df = DataFrame(np.random.randn(3, 3), columns=['A', 'B', 'C']) In [44]: (GH9322) • Index.get_indexer now supports method='pad' and method='backfill' even for any target ar- ray, not just monotonic targets. These methods also work for monotonic decreasing as well as

875457 0.51 third 1.0 0.585937 0.62 • drop_duplicates and duplicated now accept a keep keyword to target first, last, and all duplicates. The take_last keyword is deprecated, see here (GH6511, GH8505) can now accept errors keyword to suppress ValueError raised when any of label does not exist in the target data. (GH6736) In [43]: df = DataFrame(np.random.randn(3, 3), columns=['A', 'B', 'C']) In [44]: (GH9322) • Index.get_indexer now supports method='pad' and method='backfill' even for any target ar- ray, not just monotonic targets. These methods also work for monotonic decreasing as well as

when row/column names were lost when target was a list/ndarray (GH6552) • Regression in NDFrame.loc indexing when rows/columns were converted to Float64Index if target was an empty list/ndarray (GH7774) rollforward and rollback may return normal datetime (GH7502) • Bug in resample raises ValueError when target contains NaT (GH7227) • Bug in Timestamp.tz_localize resets nanosecond info (GH7534) • Bug in DatetimeIndex dtype=object on empty containers (GH5740) • df.to_csv will now return a string of the CSV data if neither a target path nor a buffer is provided (GH6061) • pd.infer_freq() will now raise a TypeError if given an

875457 0.51 third 1.0 0.585937 0.62 • drop_duplicates and duplicated now accept a keep keyword to target first, last, and all duplicates. The take_last keyword is deprecated, see here (GH6511, GH8505) can now accept errors keyword to suppress ValueError raised when any of label does not exist in the target data. (GH6736) 1.12. v0.16.1 (May 11, 2015) 179 pandas: powerful Python data analysis toolkit, (GH9322) • Index.get_indexer now supports method='pad' and method='backfill' even for any target ar- ray, not just monotonic targets. These methods also work for monotonic decreasing as well as

when row/column names were lost when target was a list/ndarray (GH6552) • Regression in NDFrame.loc indexing when rows/columns were converted to Float64Index if target was an empty list/ndarray (GH7774) rollforward and rollback may return normal datetime (GH7502) • Bug in resample raises ValueError when target contains NaT (GH7227) • Bug in Timestamp.tz_localize resets nanosecond info (GH7534) • Bug in DatetimeIndex dtype=object on empty containers (GH5740) • df.to_csv will now return a string of the CSV data if neither a target path nor a buffer is provided (GH6061) • pd.infer_freq() will now raise a TypeError if given an

dtype=object on empty containers (GH5740) • df.to_csv will now return a string of the CSV data if neither a target path nor a buffer is provided (GH6061) • pd.infer_freq() will now raise a TypeError if given an groupers (e.g. groups was missing) (GH3881) • Bug in multiple grouping with a TimeGrouper depending on target column order (GH6764) 1.1. v0.14.0 (May 31 , 2014) 25 pandas: powerful Python data analysis toolkit analysis toolkit, Release 0.14.0 Note that pie plot with DataFrame requires that you either specify a target column by the y argument or subplots=True. When y is specified, pie plot of selected column will

expression. This allows for formulaic evaluation. Only a single assignment is permitted. The assignment target can be a new column name or an existing column name, and it must be a valid Python identifier. In parser=’pandas’, engine=’numexpr’, truediv=True, local_dict=None, global_dict=None, resolvers=None, level=2, target=None) Evaluate a Python expression as a string using various backends. The following arithmetic traverse and add to the current scope. Most users will not need to change this parameter. target : a target object for assignment, optional, default is None essentially this is a passed in resolver

875457 0.51 third 1.0 0.585937 0.62 • drop_duplicates and duplicated now accept a keep keyword to target first, last, and all duplicates. The take_last keyword is deprecated, see here (GH6511, GH8505) can now accept errors keyword to suppress ValueError raised when any of label does not exist in the target data. (GH6736) In [43]: df = DataFrame(np.random.randn(3, 3), columns=['A', 'B', 'C']) In [44]: (GH9322) • Index.get_indexer now supports method='pad' and method='backfill' even for any target ar- ray, not just monotonic targets. These methods also work for monotonic decreasing as well as