y=16, z=17), name='D') In [198]: sjo Out[198]: x 15 y 16 z 17 Name: D, dtype: int64 Column oriented (the default for DataFrame) serializes the data as nested JSON objects with column labels acting "y":5,"z":6},"C":{"x":7,"y":8,"z":9}}' # Not available for Series Index oriented (the default for Series) similar to column oriented but the index labels are now primary: In [200]: dfjo.to_json(orient="index") "B":6, �→"C":9}}' In [201]: sjo.to_json(orient="index") Out[201]: '{"x":15,"y":16,"z":17}' Record oriented serializes the data to a JSON array of column -> value records, index labels are not included. This

reduce=True (GH8735). • Allow passing kwargs to the interpolation methods (GH10378). • Improved error message when concatenating an empty iterable of Dataframe objects (GH9157) • pd.read_csv can now read bz2-compressed available from Yahoo and when it receives no data from Yahoo (GH8761), (GH8783). • Unclear error message in csv parsing when passing dtype and names and the parsed data is a different data type (GH8833) unchanged) (GH7542) • Bug in rolling_count() and expanding_*() functions unnecessarily producing error message for zero-length data (GH8056) • Bug in rolling_apply() and expanding_apply() interpreting min_periods=0

available from Yahoo and when it receives no data from Yahoo (GH8761), (GH8783). • Unclear error message in csv parsing when passing dtype and names and the parsed data is a different data type (GH8833) unchanged) (GH7542) • Bug in rolling_count() and expanding_*() functions unnecessarily producing error message for zero-length data (GH8056) • Bug in rolling_apply() and expanding_apply() interpreting min_periods=0 (GH8080) • Bug in expanding_std() and expanding_var() for a single value producing a confusing error message (GH7900) • Bug in rolling_std() and rolling_var() for a single value producing 0 rather than NaN

unchanged) (GH7542) • Bug in rolling_count() and expanding_*() functions unnecessarily producing error message for zero-length data (GH8056) • Bug in rolling_apply() and expanding_apply() interpreting min_periods=0 (GH8080) • Bug in expanding_std() and expanding_var() for a single value producing a confusing error message (GH7900) • Bug in rolling_std() and rolling_var() for a single value producing 0 rather than NaN take the wrong path, and produce a DataFrame instead of a Series (GH7929) • Bug in groupby error message when a DataFrame grouping column is duplicated (GH7511) 1.2. v0.15.0 (October 18, 2014) 33 pandas:

raising a ValueError (GH12259) • read_stata() and StataReader raise with a more explicit error message when reading Stata files with repeated value labels when convert_categoricals=True (GH13923) • DataFrame warn=True, and the instance has a non- zero number of nanoseconds, previously this would print a message to stdout (GH14101). 1.1. v0.19.0 (October 2, 2016) 33 pandas: powerful Python data analysis toolkit • Bug in index coercion when falling back from RangeIndex construction (GH12893) • Better error message in window functions when invalid argument (e.g. a float window) is passed (GH12669) • Bug in slicing

raising a ValueError (GH12259) • read_stata() and StataReader raise with a more explicit error message when reading Stata files with repeated value labels when convert_categoricals=True (GH13923) • DataFrame warn=True, and the instance has a non- zero number of nanoseconds, previously this would print a message to stdout (GH14101). • Series.unique() with datetime and timezone now returns return array of Timestamp • Bug in index coercion when falling back from RangeIndex construction (GH12893) • Better error message in window functions when invalid argument (e.g. a float window) is passed (GH12669) • Bug in slicing

var where calculation is inaccurate with a zero-valued array (GH18430) 1.1.5.6 Reshaping • Error message in pd.merge_asof() for key datatype mismatch now includes datatype of left and right key (GH18068) future version of pandas rename_categories will change to treat them as dict-like. Follow the warning message’s recommendations for writing future-proof code. In [33]: c.rename_categories(pd.Series([0, 1], Previously returned False in all cases. (GH16554) • read_excel() raises ImportError with a better message if xlrd is not installed. (GH17613) • DataFrame.assign() will preserve the original order of **kwargs

more clear error message when merge keys are categoricals that are not equal (GH26136) • pandas.core.window.Rolling() supports exponential (or Poisson) window type (GH21303) • Error message for missing required given non-unique, monotonic data (GH27136). • Improved performance of pd.read_json() for index-oriented data. (GH26773) • Improved performance of MultiIndex.shape() (GH27384). 1.6 Bug fixes 1.6.1 Categorical attribute of several methods of Series.str, which were set incorrectly (GH23551) • Improved error message when passing Series of wrong dtype to Series.str.cat() (GH22722) • 1.6. Bug fixes 27 pandas: powerful

more clear error message when merge keys are categoricals that are not equal (GH26136) • pandas.core.window.Rolling() supports exponential (or Poisson) window type (GH21303) • Error message for missing required given non-unique, monotonic data (GH27136). • Improved performance of pd.read_json() for index-oriented data. (GH26773) • Improved performance of MultiIndex.shape() (GH27384). 1.6 Bug fixes 1.6.1 Categorical attribute of several methods of Series.str, which were set incorrectly (GH23551) • Improved error message when passing Series of wrong dtype to Series.str.cat() (GH22722) • 1.6. Bug fixes 27 pandas: powerful

lines in the file (GH14515) • Bug in pd.read_csv for the Python engine in which an unhelpful error message was being raised when multi-char delimiters were not being respected with quotes (GH14582) • Fix SAS file incrementally. • Bug in pd.read_csv for the Python engine in which an unhelpful error message was being raised when skipfooter was not being respected by Python’s CSV library (GH13879) • Bug raising a ValueError (GH12259) • read_stata() and StataReader raise with a more explicit error message when reading Stata files with repeated value labels when convert_categoricals=True (GH13923) • DataFrame