DataFrame.to_string() where values were truncated using display options instead of outputting the full content (GH9784) • Bug in DataFrame.to_json() where a datetime column label would not be written out in with parse_dates. In [113]: content = """\ .....: a .....: 2000-01-01T00:00:00+05:00 .....: 2000-01-01T00:00:00+06:00""" .....: In [114]: df = pd.read_csv(StringIO(content), parse_dates=['a']) In [115]: partially-applied to_datetime() with utc=True as the date_parser. In [116]: df = pd.read_csv(StringIO(content), parse_dates=['a'], .....: date_parser=lambda col: pd.to_datetime(col, utc=True)) .....: In [117]:

shown (default: 10, i.e. the first and last 5 rows). This dual option allows to still see the full content of relatively small objects (e.g. df.head(20) shows all 20 rows), while giving a brief repr for large DataFrame.to_html() where values were truncated using display options instead of outputting the full content (GH17004) • Fixed bug in missing text when using to_clipboard() if copying utf-16 characters in with parse_dates. In [110]: content = """\ .....: a .....: 2000-01-01T00:00:00+05:00 .....: 2000-01-01T00:00:00+06:00""" .....: In [111]: df = pd.read_csv(StringIO(content), parse_dates=['a']) In [112]:

with parse_dates. In [113]: content = """\ .....: a .....: 2000-01-01T00:00:00+05:00 .....: 2000-01-01T00:00:00+06:00""" .....: In [114]: df = pd.read_csv(StringIO(content), parse_dates=['a']) In [115]: partially-applied to_datetime() with utc=True as the date_parser. In [116]: df = pd.read_csv(StringIO(content), parse_dates=['a'], .....: date_parser=lambda col: pd.to_datetime(col, utc=True)) .....: In [117]: read_json('test.json', orient='table') In [295]: print(new_df.index.name) None 2.4.3 HTML Reading HTML content Warning: We highly encourage you to read the HTML Table Parsing gotchas below regarding the issues

with parse_dates. In [113]: content = """\ .....: a .....: 2000-01-01T00:00:00+05:00 .....: 2000-01-01T00:00:00+06:00""" .....: In [114]: df = pd.read_csv(StringIO(content), parse_dates=['a']) In [115]: partially-applied to_datetime() with utc=True as the date_parser. In [116]: df = pd.read_csv(StringIO(content), parse_dates=['a'], .....: date_parser=lambda col: pd.to_datetime(col, utc=True)) .....: In [117]: read_json('test.json', orient='table') In [295]: print(new_df.index.name) None 2.4.3 HTML Reading HTML content Warning: We highly encourage you to read the HTML Table Parsing gotchas below regarding the issues

shown (default: 10, i.e. the first and last 5 rows). This dual option allows to still see the full content of relatively small objects (e.g. df.head(20) shows all 20 rows), while giving a brief repr for large DataFrame.to_html() where values were truncated using display options instead of outputting the full content (GH17004) • Fixed bug in missing text when using to_clipboard() if copying utf-16 characters in with parse_dates. In [110]: content = """\ .....: a .....: 2000-01-01T00:00:00+05:00 .....: 2000-01-01T00:00:00+06:00""" .....: In [111]: df = pd.read_csv(StringIO(content), parse_dates=['a']) In [112]:

with parse_dates. In [113]: content = """\ .....: a .....: 2000-01-01T00:00:00+05:00 .....: 2000-01-01T00:00:00+06:00""" .....: In [114]: df = pd.read_csv(StringIO(content), parse_dates=['a']) In [115]: partially-applied to_datetime() with utc=True as the date_parser. In [116]: df = pd.read_csv(StringIO(content), parse_dates=['a'], .....: date_parser=lambda col: pd.to_datetime(col, utc=True)) .....: In [117]: read_json('test.json', orient='table') In [295]: print(new_df.index.name) None 2.1.3 HTML Reading HTML content Warning: We highly encourage you to read the HTML Table Parsing gotchas below regarding the issues

with parse_dates. In [113]: content = """\ .....: a .....: 2000-01-01T00:00:00+05:00 .....: 2000-01-01T00:00:00+06:00""" .....: In [114]: df = pd.read_csv(StringIO(content), parse_dates=['a']) In [115]: partially-applied to_datetime() with utc=True as the date_parser. In [116]: df = pd.read_csv(StringIO(content), parse_dates=['a'], .....: date_parser=lambda col: pd.to_datetime(col, utc=True)) .....: In [117]: read_json('test.json', orient='table') In [295]: print(new_df.index.name) None 2.1.3 HTML Reading HTML content Warning: We highly encourage you to read the HTML Table Parsing gotchas below regarding the issues

with parse_dates. In [113]: content = """\ .....: a .....: 2000-01-01T00:00:00+05:00 .....: 2000-01-01T00:00:00+06:00""" .....: In [114]: df = pd.read_csv(StringIO(content), parse_dates=['a']) In [115]: partially-applied to_datetime() with utc=True as the date_parser. In [116]: df = pd.read_csv(StringIO(content), parse_dates=['a'], .....: date_parser=lambda col: pd.to_datetime(col, utc=True)) .....: In [117]: read_json('test.json', orient='table') In [295]: print(new_df.index.name) None 3.1.3 HTML Reading HTML content Warning: We highly encourage you to read the HTML Table Parsing gotchas below regarding the issues

with parse_dates. In [113]: content = """\ .....: a .....: 2000-01-01T00:00:00+05:00 .....: 2000-01-01T00:00:00+06:00""" .....: In [114]: df = pd.read_csv(StringIO(content), parse_dates=["a"]) In [115]: partially-applied to_datetime() with utc=True as the date_parser. In [116]: df = pd.read_csv( .....: StringIO(content), .....: parse_dates=["a"], .....: date_parser=lambda col: pd.to_datetime(col, utc=True), ... read_json("test.json", orient="table") In [294]: print(new_df.index.name) None 2.4.3 HTML Reading HTML content Warning: We highly encourage you to read the HTML Table Parsing gotchas below regarding the issues

the default result will be an object-dtype column with strings, even with parse_dates. In [113]: content = """\ .....: a .....: 2000-01-01T00:00:00+05:00 .....: 2000-01-01T00:00:00+06:00""" .....: (continues analysis toolkit, Release 1.3.3 (continued from previous page) In [114]: df = pd.read_csv(StringIO(content), parse_dates=["a"]) In [115]: df["a"] Out[115]: 0 2000-01-01 00:00:00+05:00 1 2000-01-01 00:00:00+06:00 partially-applied to_datetime() with utc=True as the date_parser. In [116]: df = pd.read_csv( .....: StringIO(content), .....: parse_dates=["a"], .....: date_parser=lambda col: pd.to_datetime(col, utc=True), ...