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Report without Rejections and warnings #281
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feature request 💬
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sbrugman
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Jan 14, 2020
- Rejected variables can be disabled (no longer grey or strikethrough) - Warnings in the overview are automatically collapsed if over 20 item (configurable), can also be disabled completely by setting the limit to 0. (#281)
This was referenced Jan 14, 2020
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sbrugman
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Feb 14, 2020
- Progress bar added (#224) - Character analysis for Text/NLP (#278) - Themes: configuration and demo's (Orange, Dark) - Tutorial on modifying the report's structure (#362; #281, #259, #253, #234). This jupyter notebook also demonstrates how to use the Kaggle api together with pandas-profiling. - Toggle descriptions at correlations. Deprecation: - This is the last version to support Python 3.5. Stability: - The order of columns changed when sort="None" (#377, fixed). - Pandas v1.0.X is not yet supported (#367, #366, #363, #353, pinned pandas to < 1) - Improved mixed type detection (#351) - Refactor of report structures. - Correlations are more stable (e.g. Phi_k color scale now from 0-1, rows and columns with NaN values are dropped, #329). - Distinct counts exclude NaNs. - Fixed alerts in notebooks. Other improvements: - Warnings are now sorted. - Links to Binder and Google Colab are added for notebooks (#349) - The overview section is tabbed.
sbrugman
added a commit
that referenced
this issue
Feb 14, 2020
- Progress bar added (#224) - Character analysis for Text/NLP (#278) - Themes: configuration and demo's (Orange, Dark) - Tutorial on modifying the report's structure (#362; #281, #259, #253, #234). This jupyter notebook also demonstrates how to use the Kaggle api together with pandas-profiling. - Toggle descriptions at correlations. Deprecation: - This is the last version to support Python 3.5. Stability: - The order of columns changed when sort="None" (#377, fixed). - Pandas v1.0.X is not yet supported (#367, #366, #363, #353, pinned pandas to < 1) - Improved mixed type detection (#351) - Refactor of report structures. - Correlations are more stable (e.g. Phi_k color scale now from 0-1, rows and columns with NaN values are dropped, #329). - Distinct counts exclude NaNs. - Fixed alerts in notebooks. Other improvements: - Warnings are now sorted. - Links to Binder and Google Colab are added for notebooks (#349) - The overview section is tabbed.
sbrugman
added a commit
that referenced
this issue
Feb 14, 2020
- Progress bar added (#224) - Character analysis for Text/NLP (#278) - Themes: configuration and demo's (Orange, Dark) - Tutorial on modifying the report's structure (#362; #281, #259, #253, #234). This jupyter notebook also demonstrates how to use the Kaggle api together with pandas-profiling. - Toggle descriptions at correlations. Deprecation: - This is the last version to support Python 3.5. Stability: - The order of columns changed when sort="None" (#377, fixed). - Pandas v1.0.X is not yet supported (#367, #366, #363, #353, pinned pandas to < 1) - Improved mixed type detection (#351) - Refactor of report structures. - Correlations are more stable (e.g. Phi_k color scale now from 0-1, rows and columns with NaN values are dropped, #329). - Distinct counts exclude NaNs. - Fixed alerts in notebooks. Other improvements: - Warnings are now sorted. - Links to Binder and Google Colab are added for notebooks (#349) - The overview section is tabbed. * Commit for pandas-profiling v2.5.0 - Progress bar added (#224) - Character analysis for Text/NLP (#278) - Themes: configuration and demo's (Orange, Dark) - Tutorial on modifying the report's structure (#362; #281, #259, #253, #234). This jupyter notebook also demonstrates how to use the Kaggle api together with pandas-profiling. - Toggle descriptions at correlations. Deprecation: - This is the last version to support Python 3.5. Stability: - The order of columns changed when sort="None" (#377, fixed). - Pandas v1.0.X is not yet supported (#367, #366, #363, #353, pinned pandas to < 1) - Improved mixed type detection (#351) - Refactor of report structures. - Correlations are more stable (e.g. Phi_k color scale now from 0-1, rows and columns with NaN values are dropped, #329). - Distinct counts exclude NaNs. - Fixed alerts in notebooks. Other improvements: - Warnings are now sorted. - Links to Binder and Google Colab are added for notebooks (#349) - The overview section is tabbed.
chanedwin
pushed a commit
to chanedwin/pandas-profiling
that referenced
this issue
Oct 11, 2020
- Rejected variables can be disabled (no longer grey or strikethrough) - Warnings in the overview are automatically collapsed if over 20 item (configurable), can also be disabled completely by setting the limit to 0. (ydataai#281)
chanedwin
pushed a commit
to chanedwin/pandas-profiling
that referenced
this issue
Oct 11, 2020
- Progress bar added (ydataai#224) - Character analysis for Text/NLP (ydataai#278) - Themes: configuration and demo's (Orange, Dark) - Tutorial on modifying the report's structure (ydataai#362; ydataai#281, ydataai#259, ydataai#253, ydataai#234). This jupyter notebook also demonstrates how to use the Kaggle api together with pandas-profiling. - Toggle descriptions at correlations. Deprecation: - This is the last version to support Python 3.5. Stability: - The order of columns changed when sort="None" (ydataai#377, fixed). - Pandas v1.0.X is not yet supported (ydataai#367, ydataai#366, ydataai#363, ydataai#353, pinned pandas to < 1) - Improved mixed type detection (ydataai#351) - Refactor of report structures. - Correlations are more stable (e.g. Phi_k color scale now from 0-1, rows and columns with NaN values are dropped, ydataai#329). - Distinct counts exclude NaNs. - Fixed alerts in notebooks. Other improvements: - Warnings are now sorted. - Links to Binder and Google Colab are added for notebooks (ydataai#349) - The overview section is tabbed. * Commit for pandas-profiling v2.5.0 - Progress bar added (ydataai#224) - Character analysis for Text/NLP (ydataai#278) - Themes: configuration and demo's (Orange, Dark) - Tutorial on modifying the report's structure (ydataai#362; ydataai#281, ydataai#259, ydataai#253, ydataai#234). This jupyter notebook also demonstrates how to use the Kaggle api together with pandas-profiling. - Toggle descriptions at correlations. Deprecation: - This is the last version to support Python 3.5. Stability: - The order of columns changed when sort="None" (ydataai#377, fixed). - Pandas v1.0.X is not yet supported (ydataai#367, ydataai#366, ydataai#363, ydataai#353, pinned pandas to < 1) - Improved mixed type detection (ydataai#351) - Refactor of report structures. - Correlations are more stable (e.g. Phi_k color scale now from 0-1, rows and columns with NaN values are dropped, ydataai#329). - Distinct counts exclude NaNs. - Fixed alerts in notebooks. Other improvements: - Warnings are now sorted. - Links to Binder and Google Colab are added for notebooks (ydataai#349) - The overview section is tabbed.
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Is there a way to get a profile report without the warnings or rejections?
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