DataFrame Editor background coloring does not support pandas.Int*Dtype
dtypes
#21222
Closed
8 of 10 tasks
pandas.Int*Dtype
dtypes
#21222
Issue Report Checklist
conda update spyder
(orpip
, if not using Anaconda)jupyter qtconsole
(if console-related)spyder --reset
Problem Description
Introduction
Pandas nowadays has nullable types for integers etc. so that missing values can be represented without conversion to floats. An example is
pandas.Int64Dtype
described here: https://pandas.pydata.org/docs/user_guide/integer_na.html Although the concept of nullable types is relatively new and mostly non-default, it can be very useful. Moreover, some methods ofpandas.StringDtype
return nullable integers, and the documentation specifically recommends usingpandas.StringDtype
for text data.Problem
The DataFrame Editor in Spyder appears to lack background coloring support for pandas nullable integer data types.
What steps reproduce the problem?
In the IPython console, type the following:
This produces a DataFrame with the following dtypes (as printed by
df.dtypes
; hereInt64
meanspandas.Int64Dtype
):Next, double-click
df
in the Variable Explorer.What is the expected output? What do you see instead?
In the DataFrame Editor, the following is shown. In the first two columns, the data which uses traditional dtypes is correctly colored, whereas in the last two columns, the data which uses the new nullable integer type is not colored.
Versions
Dependencies
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