From 967db35f485bd9699a5316cac7a21f8fede8b225 Mon Sep 17 00:00:00 2001 From: Dror Atariah Date: Tue, 29 Aug 2017 10:18:30 +0200 Subject: [PATCH 1/2] Specify the ticks of the error bars --- doc/source/visualization.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/source/visualization.rst b/doc/source/visualization.rst index fb799c642131d..332e425492afd 100644 --- a/doc/source/visualization.rst +++ b/doc/source/visualization.rst @@ -1401,7 +1401,7 @@ Here is an example of one way to easily plot group means with standard deviation # Plot fig, ax = plt.subplots() @savefig errorbar_example.png - means.plot.bar(yerr=errors, ax=ax) + means.plot.bar(yerr=errors, ax=ax, capsize=4) .. ipython:: python :suppress: From 0289098ae20ef1c88437186d224ec11dc689a828 Mon Sep 17 00:00:00 2001 From: Dror Atariah Date: Sun, 15 Oct 2017 21:50:57 +0200 Subject: [PATCH 2/2] BUG: Fixing GH17855 --- pandas/io/sql.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/pandas/io/sql.py b/pandas/io/sql.py index 9c6d01d236c57..dbe9dc7123e96 100644 --- a/pandas/io/sql.py +++ b/pandas/io/sql.py @@ -109,7 +109,10 @@ def _handle_date_column(col, utc=None, format=None): issubclass(col.dtype.type, np.integer)): # parse dates as timestamp format = 's' if format is None else format - return to_datetime(col, errors='coerce', unit=format, utc=utc) + if '%' in format: + return to_datetime(col, errors='coerce', format=format, utc=utc) + else: + return to_datetime(col, errors='coerce', unit=format, utc=utc) elif is_datetime64tz_dtype(col): # coerce to UTC timezone # GH11216