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api/behavior api design {col_label}{any_string}{autoincrementing int} api makes sense personal information api input column names discussion requires discussion comment metadata assignees duplicate columns exist duplicate column names duplicate columns names final column names data apis consortium repeated column names makes things note duplicated column names support mangle_dupe_cols=false datapythonista mentioned current api type projects projects milestone make things duplicate columns columns exist eventually deprecate action type load data column names repeated names pandas consistent handling operation results make obsolete consistency mangle_dupe_cols parameter simply remove mangle_dupe_cols add implemented mangle_dupe_cols andthe code duplicated columns loading data loads data column {col} orient='split' read_xml drops backward compatibility deprecation period core team errors keyword understanding correctly jeff suggested

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DiscussionForumPosting:
      context:https://schema.org
      headline:API: Consistent handling of duplicate input columns
      articleBody:When loading data into pandas with `pandas.read_X()` methods, the behavior when duplicate columns exist changes depending on the format. For `read_csv`, `read_fwf` and `read_excel` we have a `mangle_dupe_cols` parameter that we can provide. By default it appends `.1`, `.2`... to duplicated column names. Setting it to `False` raises an exception about not being implemented. `html` also appends `.1`... but the option is not provided. `read_json(orient='split')` loads data with the duplicate column names. `read_xml` drops the columns if they are duplicated (I assume one columns keeps overwriting the previous with the same name). Personally, I think we should have consistency among all them. What I would do is to control this with an option (e.g. `io.duplicate_columns`. Could also be an argument for all the `read_` methods, but I think these methods have already too many arguments, and I think the number of cases when users want to change this to be small, and very unlikely that they want to have different ways of handling duplicate column names in different calls to read methods. Whether it's an option or an argument, we could allow the next options (feel free to propose better names): - `raise`: If duplicate column names exist, raise an exception - `drop`: Keep one (maybe the first) and ignore the rest - `allow` Load data with duplicate columns. Based on discussions in the data apis consortium and #13262, I'd add this for backward compatibility only, but we shouldn't probably allow duplicate column names after a deprecation period. Or we can simply remove this option - `{col}.{i}`, `{col}_{i}`...: Allow appending an autonumeric with a custom format. By default, `'{col}.{i}'` could be used, as this seems to be the preferred way based on the current API. This would address #8908, I think it'd be good to have a single function that receives the input column names and return the final column names (indices of columns to use may also be needed, for cases like `drop`), or raises when appropriate. And all `read_` functions should use it if the format can have duplicate columns names. Thoughts?
      author:
         url:https://github.com/datapythonista
         type:Person
         name:datapythonista
      datePublished:2022-07-14T10:54:45.000Z
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      url:https://github.com/47718/pandas/issues/47718
      context:https://schema.org
      headline:API: Consistent handling of duplicate input columns
      articleBody:When loading data into pandas with `pandas.read_X()` methods, the behavior when duplicate columns exist changes depending on the format. For `read_csv`, `read_fwf` and `read_excel` we have a `mangle_dupe_cols` parameter that we can provide. By default it appends `.1`, `.2`... to duplicated column names. Setting it to `False` raises an exception about not being implemented. `html` also appends `.1`... but the option is not provided. `read_json(orient='split')` loads data with the duplicate column names. `read_xml` drops the columns if they are duplicated (I assume one columns keeps overwriting the previous with the same name). Personally, I think we should have consistency among all them. What I would do is to control this with an option (e.g. `io.duplicate_columns`. Could also be an argument for all the `read_` methods, but I think these methods have already too many arguments, and I think the number of cases when users want to change this to be small, and very unlikely that they want to have different ways of handling duplicate column names in different calls to read methods. Whether it's an option or an argument, we could allow the next options (feel free to propose better names): - `raise`: If duplicate column names exist, raise an exception - `drop`: Keep one (maybe the first) and ignore the rest - `allow` Load data with duplicate columns. Based on discussions in the data apis consortium and #13262, I'd add this for backward compatibility only, but we shouldn't probably allow duplicate column names after a deprecation period. Or we can simply remove this option - `{col}.{i}`, `{col}_{i}`...: Allow appending an autonumeric with a custom format. By default, `'{col}.{i}'` could be used, as this seems to be the preferred way based on the current API. This would address #8908, I think it'd be good to have a single function that receives the input column names and return the final column names (indices of columns to use may also be needed, for cases like `drop`), or raises when appropriate. And all `read_` functions should use it if the format can have duplicate columns names. Thoughts?
      author:
         url:https://github.com/datapythonista
         type:Person
         name:datapythonista
      datePublished:2022-07-14T10:54:45.000Z
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      url:https://github.com/47718/pandas/issues/47718
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      url:https://github.com/datapythonista
      name:datapythonista
      url:https://github.com/datapythonista
      name:datapythonista
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