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__pycache__ /
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* .py [cod ]
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* $py.class
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+ .DS_Store
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# C extensions
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* .so
Original file line number Diff line number Diff line change @@ -52,15 +52,15 @@ Tabs and single document mode allow you to focus.
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JupyterLab has a powerful and extensible architecture for handling a wide range of file formats:
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* CSV
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- - ` iris.csv ` (small)
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+ - ` ./data/ iris.csv` (small)
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- ` TCGA_Data ` (small to medium)
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- - Urban_Data_Challenge: ` big.csv `
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+ - Urban_Data_Challenge: ` data/ big.csv`
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* Images
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- - ` hubble.png `
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+ - ` data/ hubble.png`
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* Vega-Lite
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- - ` vega.vl.json `
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- * Open DC museum GeoJSON file from [ OpenData DC] ( http://opendata.dc.gov/datasets/2e65fc16edc3481989d2cc17e6f8c533_54 ) : ` Museums_in_DC.geojson `
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- * Notebook demonstrating bqplot widgets: ` bqplot.ipynb `
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+ - ` data/ vega.vl.json`
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+ * Open DC museum GeoJSON file from [ OpenData DC] ( http://opendata.dc.gov/datasets/2e65fc16edc3481989d2cc17e6f8c533_54 ) : ` data/ Museums_in_DC.geojson`
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+ * Notebook demonstrating bqplot widgets: ` notebooks/ bqplot.ipynb`
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## 5) Plugin architecture
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rm -rf notebooks
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rm -rf narrative
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rm -rf slides
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- rm demo/notebooks/Data.ipynb
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rm demo/notebooks/Julia.ipynb
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jupyter lab clean
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demo :
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files :
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- - data/iris.csv
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- - data/1024px-Hubble_Interacting_Galaxy_AM_0500-620_(2008-04-24).jpg
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- - data/Museums_in_DC.geojson
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- - data/japan_meterological_agency_201707211555.json
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- - data/zika_assembled_genomes.fasta
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- slides/jupyterlab-slides.pdf
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- narrative/jupyterlab.md
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- narrative/markdown_python.md
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folders :
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demofiles/TCGA/Extra_Data : TCGA_Data
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- demofiles/Urban-Data-Challenge/public-transportation/geneva : Urban_Data_Challenge
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notebooks : notebooks
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+ data : data
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rename :
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- demofiles/urban-data-challenge /public-transportation/geneva/schedule-real-time.csv : big.csv
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+ demofiles/Urban-Data-Challenge /public-transportation/geneva/schedule-real-time.csv : big.csv
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demofiles/tcga/extra_data/c2.cp.v3.0.symbols_edit.csv : smaller.csv
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demofiles/altair/altair/v1/examples/json/bar.vl.json : vega.vl.json
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demofiles/PythonDataScienceHandbook/notebooks/03.08-Aggregation-and-Grouping.ipynb : notebooks/pandas.ipynb
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