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Cannot style.background_gradient
on an Int64
column
#28869
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Labels
ExtensionArray
Extending pandas with custom dtypes or arrays.
good first issue
Needs Tests
Unit test(s) needed to prevent regressions
Styler
conditional formatting using DataFrame.style
Comments
immaxchen
added a commit
to immaxchen/pandas
that referenced
this issue
Oct 27, 2019
Resolve pandas-dev#12145 and pandas-dev#28869 For `vmin` and `vmax` use the same implementation in `Styler.bar` For dtype `Int64` issue, deprecated `.values` and use `.to_numpy` instead Here explicitly assign the dtype to float since we are doing normalize
5 tasks
TomAugspurger
pushed a commit
that referenced
this issue
Nov 3, 2019
…29245) * ENH: Styler.background_gradient to accept vmin vmax and dtype Int64 Resolve #12145 and #28869 For `vmin` and `vmax` use the same implementation in `Styler.bar` For dtype `Int64` issue, deprecated `.values` and use `.to_numpy` instead Here explicitly assign the dtype to float since we are doing normalize
Reksbril
pushed a commit
to Reksbril/pandas
that referenced
this issue
Nov 18, 2019
…andas-dev#29245) * ENH: Styler.background_gradient to accept vmin vmax and dtype Int64 Resolve pandas-dev#12145 and pandas-dev#28869 For `vmin` and `vmax` use the same implementation in `Styler.bar` For dtype `Int64` issue, deprecated `.values` and use `.to_numpy` instead Here explicitly assign the dtype to float since we are doing normalize
proost
pushed a commit
to proost/pandas
that referenced
this issue
Dec 19, 2019
…andas-dev#29245) * ENH: Styler.background_gradient to accept vmin vmax and dtype Int64 Resolve pandas-dev#12145 and pandas-dev#28869 For `vmin` and `vmax` use the same implementation in `Styler.bar` For dtype `Int64` issue, deprecated `.values` and use `.to_numpy` instead Here explicitly assign the dtype to float since we are doing normalize
proost
pushed a commit
to proost/pandas
that referenced
this issue
Dec 19, 2019
…andas-dev#29245) * ENH: Styler.background_gradient to accept vmin vmax and dtype Int64 Resolve pandas-dev#12145 and pandas-dev#28869 For `vmin` and `vmax` use the same implementation in `Styler.bar` For dtype `Int64` issue, deprecated `.values` and use `.to_numpy` instead Here explicitly assign the dtype to float since we are doing normalize
Works now on master |
Can confirm it's fixed now |
@attack68 is there a test for this? If not, best to leave it open til then |
@MarcoGorelli Isn't this the test integrated as part of the PR 29245 above:
That's why I though this was closeable? |
@attack68 my bad, thanks! |
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Labels
ExtensionArray
Extending pandas with custom dtypes or arrays.
good first issue
Needs Tests
Unit test(s) needed to prevent regressions
Styler
conditional formatting using DataFrame.style
Problem description
Similarly to #25580, the newer Int64 backend is missing some basic functionality.
Expected: values.min() is available, gradients are displayed
Actual:
and full stack of the
background_gradient
error:Output of
pd.show_versions()
commit: None
python: 3.6.8.final.0
python-bits: 64
OS: Linux
OS-release: 3.10.0-1062.1.1.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
pandas: 0.24.2
pytest: 5.0.1
pip: 19.2.3
setuptools: 41.0.1
Cython: None
numpy: 1.16.3
scipy: 1.3.0
pyarrow: None
xarray: None
IPython: 7.5.0
sphinx: None
patsy: None
dateutil: 2.8.0
pytz: 2019.1
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 3.1.0
openpyxl: None
xlrd: 1.2.0
xlwt: None
xlsxwriter: None
lxml.etree: 4.3.3
bs4: None
html5lib: None
sqlalchemy: 1.3.3
pymysql: None
psycopg2: None
jinja2: 2.10.1
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None
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