(GH10531) • Bug in Index subtypes (such as PeriodIndex) not returning their own type for .drop and .insert methods (GH10620) • Bug in algos.outer_join_indexer when right array is empty (GH10618) • Bug in Series(["a", "b", "c"]) In [91]: s.loc[0] = None In [92]: s Out[92]: 0 None 1 b 2 c dtype: object To insert a NaN, you must explicitly use np.nan. See the docs. • In prior versions, updating a pandas object rule (GH5897) • Bug in Panel.apply with a multi-index as an axis (GH7469) • Bug in DatetimeIndex.insert doesn’t preserve name and tz (GH7299) • Bug in DatetimeIndex.asobject doesn’t preserve name (GH7299)

and now performs conversion by default. (GH3907) • Add the keyword allow_duplicates to DataFrame.insert to allow a duplicate column to be inserted if True, default is False (same as prior to 0.12) (GH3679) dtypes is fixed (GH3602) – Allow insert/delete to non-unique columns (GH3679) – Non-unique indexing with a slice via loc and friends fixed (GH3659) – Allow insert/delete to non-unique columns (GH3679) container for Series, and Panel is a container for DataFrame objects. We would like to be able to insert and remove objects from these containers in a dictionary-like fashion. Also, we would like sensible

Series(["a", "b", "c"]) In [96]: s.loc[0] = None In [97]: s Out[97]: 0 None 1 b 2 c dtype: object To insert a NaN, you must explicitly use np.nan. See the docs. 1.3. v0.15.0 (October 18, 2014) 29 pandas: rule (GH5897) • Bug in Panel.apply with a multi-index as an axis (GH7469) • Bug in DatetimeIndex.insert doesn’t preserve name and tz (GH7299) • Bug in DatetimeIndex.asobject doesn’t preserve name (GH7299) and now performs conversion by default. (GH3907) • Add the keyword allow_duplicates to DataFrame.insert to allow a duplicate column to be inserted if True, default is False (same as prior to 0.12) (GH3679)

Series(["a", "b", "c"]) In [96]: s.loc[0] = None In [97]: s Out[97]: 0 None 1 b 2 c dtype: object To insert a NaN, you must explicitly use np.nan. See the docs. • In prior versions, updating a pandas object rule (GH5897) • Bug in Panel.apply with a multi-index as an axis (GH7469) • Bug in DatetimeIndex.insert doesn’t preserve name and tz (GH7299) • Bug in DatetimeIndex.asobject doesn’t preserve name (GH7299) and now performs conversion by default. (GH3907) • Add the keyword allow_duplicates to DataFrame.insert to allow a duplicate column to be inserted if True, default is False (same as prior to 0.12) (GH3679)

identical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1579 pandas.Index.insert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1579 pandas.Index identical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1605 pandas.CategoricalIndex.insert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1606 pandas.CategoricalIndex identical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1636 pandas.MultiIndex.insert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1636 pandas.MultiIndex

identical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1575 pandas.Index.insert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1576 pandas.Index identical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1602 pandas.CategoricalIndex.insert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1602 pandas.CategoricalIndex identical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1631 pandas.MultiIndex.insert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1631 pandas.MultiIndex

container for Series, and Panel is a container for DataFrame objects. We would like to be able to insert and remove objects from these containers in a dictionary-like fashion. Also, we would like sensible NaN You can insert raw ndarrays but their length must match the length of the DataFrame’s index. By default, columns get inserted at the end. The insert function is available to insert at a particular particular location in the columns: In [287]: df.insert(1, ’bar’, df[’one’]) In [288]: df Out[288]: one bar flag foo one_trunc a 1 1 False bar 1 b 2 2 False bar 2 c 3 3 True bar NaN d NaN NaN False bar

container for Series, and Panel is a container for DataFrame objects. We would like to be able to insert and remove objects from these containers in a dictionary-like fashion. Also, we would like sensible NaN You can insert raw ndarrays but their length must match the length of the DataFrame’s index. By default, columns get inserted at the end. The insert function is available to insert at a particular particular location in the columns: In [287]: df.insert(1, ’bar’, df[’one’]) In [288]: df Out[288]: one bar flag foo one_trunc a 1 1 False bar 1 b 2 2 False bar 2 c 3 3 True bar NaN d NaN NaN False bar

and now performs conversion by default. (GH3907) • Add the keyword allow_duplicates to DataFrame.insert to allow a duplicate column to be inserted if True, default is False (same as prior to 0.12) (GH3679) dtypes is fixed (GH3602) – Allow insert/delete to non-unique columns (GH3679) – Non-unique indexing with a slice via loc and friends fixed (GH3659) – Allow insert/delete to non-unique columns (GH3679) container for Series, and Panel is a container for DataFrame objects. We would like to be able to insert and remove objects from these containers in a dictionary-like fashion. Also, we would like sensible

container for Series, and Panel is a container for DataFrame objects. We would like to be able to insert and remove objects from these containers in a dictionary-like fashion. Also, we would like sensible NaN You can insert raw ndarrays but their length must match the length of the DataFrame’s index. By default, columns get inserted at the end. The insert function is available to insert at a particular particular location in the columns: In [287]: df.insert(1, ’bar’, df[’one’]) In [288]: df Out[288]: one bar flag foo one_trunc a 1 1 False bar 1 b 2 2 False bar 2 c 3 3 True bar NaN d NaN NaN False bar