diff --git a/demo/World population.Rmd b/demo/World population.Rmd index f0f803077..e70a0c17d 100644 --- a/demo/World population.Rmd +++ b/demo/World population.Rmd @@ -2,12 +2,12 @@ jupyter: jupytext: cell_markers: region,endregion - formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc + formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc,.myst.md:myst text_representation: extension: .Rmd format_name: rmarkdown - format_version: '1.1' - jupytext_version: 1.1.0 + format_version: '1.2' + jupytext_version: 1.11.1 kernelspec: display_name: Python 3 language: python diff --git a/demo/World population.ipynb b/demo/World population.ipynb index a87d30f7f..6487ed8a1 100644 --- a/demo/World population.ipynb +++ b/demo/World population.ipynb @@ -1435,7 +1435,7 @@ "metadata": { "jupytext": { "cell_markers": "region,endregion", - "formats": "ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc" + "formats": "ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc,.myst.md:myst" }, "kernelspec": { "display_name": "Python 3", diff --git a/demo/World population.lgt.py b/demo/World population.lgt.py index e485bb043..b6751ea20 100644 --- a/demo/World population.lgt.py +++ b/demo/World population.lgt.py @@ -2,25 +2,29 @@ # jupyter: # jupytext: # cell_markers: region,endregion -# formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc +# formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc,.myst.md:myst # text_representation: # extension: .py # format_name: light -# format_version: '1.4' -# jupytext_version: 1.1.0 +# format_version: '1.5' +# jupytext_version: 1.11.1 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- -# # A quick insight at world population -# -# ## Collecting population data -# -# In the below we retrieve population data from the -# [World Bank](http://www.worldbank.org/) -# using the [wbdata](https://github.com/OliverSherouse/wbdata) python package +# region [markdown] +""" +# A quick insight at world population + +## Collecting population data + +In the below we retrieve population data from the +[World Bank](http://www.worldbank.org/) +using the [wbdata](https://github.com/OliverSherouse/wbdata) python package +""" +# endregion # region import pandas as pd diff --git a/demo/World population.md b/demo/World population.md index a11034039..30eb95f18 100644 --- a/demo/World population.md +++ b/demo/World population.md @@ -2,12 +2,12 @@ jupyter: jupytext: cell_markers: region,endregion - formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc + formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc,.myst.md:myst text_representation: extension: .md format_name: markdown - format_version: '1.1' - jupytext_version: 1.1.0 + format_version: '1.3' + jupytext_version: 1.11.1 kernelspec: display_name: Python 3 language: python diff --git a/demo/World population.myst.md b/demo/World population.myst.md index 721b8b05e..59b03b05c 100644 --- a/demo/World population.myst.md +++ b/demo/World population.myst.md @@ -1,11 +1,12 @@ --- jupytext: + cell_markers: region,endregion formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc,.myst.md:myst text_representation: - extension: '.md' + extension: .md format_name: myst - format_version: '0.7' - jupytext_version: 1.4.0+dev + format_version: 0.13 + jupytext_version: 1.11.1 kernelspec: display_name: Python 3 language: python @@ -95,13 +96,6 @@ plt.show() ## Stacked bar plot with plotly -+++ - -Stacked area plots (with cumulated values computed depending on -selected legends) are -[on their way](https://github.com/plotly/plotly.js/pull/2960) at Plotly. For -now we just do a stacked bar plot. - ```{code-cell} ipython3 import plotly.offline as offline import plotly.graph_objs as go @@ -110,10 +104,9 @@ offline.init_notebook_mode() ``` ```{code-cell} ipython3 -bars = [go.Bar(x=population.index, y=population[zone], name=zone) +data = [go.Scatter(x=population.index, y=population[zone], name=zone, stackgroup='World') for zone in zones] -fig = go.Figure(data=bars, - layout=go.Layout(title='World population', - barmode='stack')) +fig = go.Figure(data=data, + layout=go.Layout(title='World population')) offline.iplot(fig) ``` diff --git a/demo/World population.pandoc.md b/demo/World population.pandoc.md index 87de7e280..702eec65e 100644 --- a/demo/World population.pandoc.md +++ b/demo/World population.pandoc.md @@ -1,13 +1,13 @@ --- jupyter: jupytext: - cell_markers: 'region,endregion' - formats: 'ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc' + cell_markers: region,endregion + formats: "ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc,.myst.md:myst" text_representation: - extension: '.md' + extension: .md format_name: pandoc - format_version: '2.7.2' - jupytext_version: '1.1.0' + format_version: 2.11.4 + jupytext_version: 1.11.1 kernelspec: display_name: Python 3 language: python diff --git a/demo/World population.pct.py b/demo/World population.pct.py index f74c8eee5..bfe3b4b6f 100644 --- a/demo/World population.pct.py +++ b/demo/World population.pct.py @@ -2,12 +2,12 @@ # jupyter: # jupytext: # cell_markers: region,endregion -# formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc +# formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc,.myst.md:myst # text_representation: # extension: .py # format_name: percent -# format_version: '1.2' -# jupytext_version: 1.1.0 +# format_version: '1.3' +# jupytext_version: 1.11.1 # kernelspec: # display_name: Python 3 # language: python @@ -15,13 +15,15 @@ # --- # %% [markdown] -# # A quick insight at world population -# -# ## Collecting population data -# -# In the below we retrieve population data from the -# [World Bank](http://www.worldbank.org/) -# using the [wbdata](https://github.com/OliverSherouse/wbdata) python package +""" +# A quick insight at world population + +## Collecting population data + +In the below we retrieve population data from the +[World Bank](http://www.worldbank.org/) +using the [wbdata](https://github.com/OliverSherouse/wbdata) python package +""" # %% import pandas as pd diff --git a/demo/World population.spx.py b/demo/World population.spx.py index 9fe5da91b..c20a321e3 100644 --- a/demo/World population.spx.py +++ b/demo/World population.spx.py @@ -2,12 +2,12 @@ # jupyter: # jupytext: # cell_markers: region,endregion -# formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc +# formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc,.myst.md:myst # text_representation: # extension: .py # format_name: sphinx # format_version: '1.1' -# jupytext_version: 1.1.0 +# jupytext_version: 1.11.1 # kernelspec: # display_name: Python 3 # language: python