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The KDE Plot of a series with missing values fails, producing an empty plot whereas the histogram is able to drop the missing values.
Expected Output
The KDE Plot is generated when the missing values are removed manually or by using dropna()
According to the Pandas doc on plotting with missing data, the default way NaNs are handled is by dropping them. But this does not happen - an empty plot is generated
BUG: Fixed KDE plot to ignore missing values
closes#14821
* fixed kde plot to ignore the missing values
* added comment to elaborate the changes made
* added a release note in whatsnew/0.19.2
* added test to check for missing values and cleaned up whatsnew doc
* added comment to refer the issue
* modified to fit lint checks
* replaced ._xorig with .get_xdata()
ischurov
pushed a commit
to ischurov/pandas
that referenced
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Dec 19, 2016
BUG: Fixed KDE plot to ignore missing values
closespandas-dev#14821
* fixed kde plot to ignore the missing values
* added comment to elaborate the changes made
* added a release note in whatsnew/0.19.2
* added test to check for missing values and cleaned up whatsnew doc
* added comment to refer the issue
* modified to fit lint checks
* replaced ._xorig with .get_xdata()
BUG: Fixed KDE plot to ignore missing values
closespandas-dev#14821
* fixed kde plot to ignore the missing values
* added comment to elaborate the changes made
* added a release note in whatsnew/0.19.2
* added test to check for missing values and cleaned up whatsnew doc
* added comment to refer the issue
* modified to fit lint checks
* replaced ._xorig with .get_xdata()
(cherry picked from commit 033d345)
The KDE Plot of a series with missing values fails, producing an empty plot whereas the histogram is able to drop the missing values.
Expected Output
dropna()
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Linux
OS-release: 3.13.0-92-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
pandas: 0.19.1
nose: 1.3.7
pip: 9.0.1
setuptools: 23.0.0
Cython: 0.24
numpy: 1.11.1
scipy: 0.17.1
statsmodels: 0.6.1
xarray: None
IPython: 4.2.0
sphinx: 1.4.1
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.4
blosc: None
bottleneck: 1.1.0
tables: 3.2.2
numexpr: 2.6.0
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.2
lxml: 3.6.0
bs4: 4.4.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.13
pymysql: None
psycopg2: 2.6.2 (dt dec pq3 ext lo64)
jinja2: 2.8
boto: 2.40.0
pandas_datareader: None
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