Add an option to export results as a small main page with pointers to linked resources #253
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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
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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
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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. * 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.
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chanedwin
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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 your feature request related to a problem? Please describe.
Yes : It's related to a problem on using profiling outputs on big dataframes.
When using pandas-profiling on dataframes with many columns, the size of the resulting HTML document can be huge. For instance, a Pandas dataframe with ~1700 columns produced a single ~1.2 GB HTML file. Such a file can hardly be rendered on Web browsers, so the output is useless.
Describe the solution you'd like
I believe it's easier for Web browsers to manage HTML resources with linked sub-resources. Therefore, it could be interesting for the user to use pandas-profiling in such a way a zipped directory is generated, with a small main page pointing to image files and/or sub pages, since it would be more efficient for big outputs.
Describe alternatives you've considered
My computer has a 16 GB of RAM, and I tested modern versions of Firefox and Chrome, so expecting to problem to disappear by using a better hardware/software is probably not an option.
Additional context
Thank you.
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