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Keywords {🔍}

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open issues discussing personal information bug sql-compatible database major architectural move comment metadata assignees introduces null logic missing-data np na assert pd pandas breaks setting incompatible values solutions projects milestone type projects bug exists import pandas na/null null-values triage issue dtype na ist assert pd data type nullable type latest version master branch overarching principle make sense reading cvs mailing list conclusion reached buggier/unstable stay opt tough nut milestone relationships default assignment series/frames nullable types passes mock_data github expected behavior bug numeric column numpy types pandas dataframe[int64] numpy dtypes column type default mock_data mock_data = pd change column'

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DiscussionForumPosting:
      context:https://schema.org
      headline:BUG: `pd.NA` when it replaces a value in a column, changes its type to "object"
      articleBody:### - [X] I have checked that this issue has not already been reported. - [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas. - [ ] I have confirmed this bug exists on the master branch of pandas. ### Reproducible Example ```python import pandas as pd mock_data = pd.DataFrame({ 'date': ['0', '1', '2', '3'], 'value': [1, 2, 1, 1.5] }) assert pd.api.types.is_numeric_dtype(mock_data.value) # passes mock_data_pd_na.loc[2, 'value'] = pd.NA assert pd.api.types.is_numeric_dtype(mock_data.value) # breaks ``` ### Issue Description Changing one value in a column with an `NA`/`NULL` should not change column's data type. That seems reasonable. Also, it seems the functionality is already there. I am not entirely sure if this is a bug or a feature. Essentially it is due to the default assignment of a column type, which is `float64` not `pd.Float64Dtype()`. I am not sure if the migration is on the roadmap, but this bug could be an argument in its favor. ### Expected Behavior ```python mock_data = pd.DataFrame({ 'date': ['0', '1', '2', '3'], 'value': [1, 2, 1, 1.5] }) mock_data.value = mock_data.value.astype(pd.Float64Dtype()) # this should happen by default mock_data.value.dtype # Float64Dtype() mock_data.loc[2, 'value'] = pd.NA assert pd.api.types.is_numeric_dtype(mock_data.value) # still passes mock_data.value.dtype # Float64Dtype() ``` ### Installed Versions <details> ``` pandas : 1.3.4 ``` ``` INSTALLED VERSIONS ------------------ commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5 python : 3.9.7.final.0 python-bits : 64 OS : Linux OS-release : 5.11.0-34-generic Version : #36~20.04.1-Ubuntu SMP Fri Aug 27 08:06:32 UTC 2021 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8 pandas : 1.3.4 numpy : 1.21.2 pytz : 2021.3 dateutil : 2.8.2 pip : 21.3.1 setuptools : 58.2.0 Cython : None pytest : None hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : 3.0.2 IPython : 7.28.0 pandas_datareader: None bs4 : None bottleneck : None fsspec : None fastparquet : None gcsfs : None matplotlib : 3.4.3 numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : 5.0.0 pyxlsb : None s3fs : None scipy : 1.7.1 sqlalchemy : 1.4.25 tables : None tabulate : 0.8.9 xarray : None xlrd : None xlwt : None numba : None ``` </details>
      author:
         url:https://github.com/Demetrio92
         type:Person
         name:Demetrio92
      datePublished:2021-10-27T00:24:43.000Z
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      url:https://github.com/44199/pandas/issues/44199
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      headline:BUG: `pd.NA` when it replaces a value in a column, changes its type to "object"
      articleBody:### - [X] I have checked that this issue has not already been reported. - [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas. - [ ] I have confirmed this bug exists on the master branch of pandas. ### Reproducible Example ```python import pandas as pd mock_data = pd.DataFrame({ 'date': ['0', '1', '2', '3'], 'value': [1, 2, 1, 1.5] }) assert pd.api.types.is_numeric_dtype(mock_data.value) # passes mock_data_pd_na.loc[2, 'value'] = pd.NA assert pd.api.types.is_numeric_dtype(mock_data.value) # breaks ``` ### Issue Description Changing one value in a column with an `NA`/`NULL` should not change column's data type. That seems reasonable. Also, it seems the functionality is already there. I am not entirely sure if this is a bug or a feature. Essentially it is due to the default assignment of a column type, which is `float64` not `pd.Float64Dtype()`. I am not sure if the migration is on the roadmap, but this bug could be an argument in its favor. ### Expected Behavior ```python mock_data = pd.DataFrame({ 'date': ['0', '1', '2', '3'], 'value': [1, 2, 1, 1.5] }) mock_data.value = mock_data.value.astype(pd.Float64Dtype()) # this should happen by default mock_data.value.dtype # Float64Dtype() mock_data.loc[2, 'value'] = pd.NA assert pd.api.types.is_numeric_dtype(mock_data.value) # still passes mock_data.value.dtype # Float64Dtype() ``` ### Installed Versions <details> ``` pandas : 1.3.4 ``` ``` INSTALLED VERSIONS ------------------ commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5 python : 3.9.7.final.0 python-bits : 64 OS : Linux OS-release : 5.11.0-34-generic Version : #36~20.04.1-Ubuntu SMP Fri Aug 27 08:06:32 UTC 2021 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8 pandas : 1.3.4 numpy : 1.21.2 pytz : 2021.3 dateutil : 2.8.2 pip : 21.3.1 setuptools : 58.2.0 Cython : None pytest : None hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : 3.0.2 IPython : 7.28.0 pandas_datareader: None bs4 : None bottleneck : None fsspec : None fastparquet : None gcsfs : None matplotlib : 3.4.3 numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : 5.0.0 pyxlsb : None s3fs : None scipy : 1.7.1 sqlalchemy : 1.4.25 tables : None tabulate : 0.8.9 xarray : None xlrd : None xlwt : None numba : None ``` </details>
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      url:https://github.com/44199/pandas/issues/44199
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