Update the Binder environment

CHANGELOG.md

@@ -2,7 +2,7 @@
 ------------------
 
 **Fixed**
-- We now use HTTPS as required by the world bank API ([#18](https://github.com/mwouts/world_bank_data/pulls/18)) - thanks to [John Cant](https://github.com/johncant) for fixing this!
+- We now use HTTPS as required by the world bank API ([#18](https://github.com/mwouts/world_bank_data/pull/18)) - thanks to [John Cant](https://github.com/johncant) for fixing this!
 
 **Added**
 - Added `__version__`

README.md

@@ -2,13 +2,9 @@
 
 [![CI](https://github.com/mwouts/world_bank_data/actions/workflows/continuous-integration.yml/badge.svg?branch=main)](https://github.com/mwouts/world_bank_data/actions)
 [![codecov.io](https://codecov.io/github/mwouts/world_bank_data/coverage.svg?branch=main)](https://codecov.io/github/mwouts/world_bank_data?branch=main)
-[![Language grade: Python](https://img.shields.io/badge/lgtm-A+-brightgreen.svg)](https://lgtm.com/projects/g/mwouts/world_bank_data/context:python)
 [![Pypi](https://img.shields.io/pypi/v/world_bank_data.svg)](https://pypi.python.org/pypi/world_bank_data)
 [![pyversions](https://img.shields.io/pypi/pyversions/world_bank_data.svg)](https://pypi.python.org/pypi/world_bank_data)
-[![Jupyter Notebook](https://img.shields.io/badge/Binder-Notebook-blue.svg)](
-    https://mybinder.org/v2/gh/mwouts/world_bank_data/main?filepath=examples%2FA%20sunburst%20plot%20of%20the%20world%20population.ipynb)
-[![JupyterLab](https://img.shields.io/badge/Binder-JupyterLab-blue.svg)](
-    https://mybinder.org/v2/gh/mwouts/world_bank_data/main?urlpath=lab)
+[![JupyterLab](https://img.shields.io/badge/Binder-JupyterLab-blue.svg)](https://mybinder.org/v2/gh/mwouts/world_bank_data/main?urlpath=lab)
 
 This is an implementation of the [World Bank API v2](https://datahelpdesk.worldbank.org/knowledgebase/articles/889386-developer-information-overview) in Python. Use this package to explore the [World Development Indicators](http://datatopics.worldbank.org/world-development-indicators/) published by the [World Bank](http://www.worldbank.org/).
 
@@ -94,9 +90,9 @@ wb.get_series('SP.POP.TOTL', date='2016', id_or_value='id', simplify_index=True)
 
 ## Ready for an interative tutorial?
 
-Go to our [Binder](https://mybinder.org/v2/gh/mwouts/world_bank_data/main) and run either this [README](https://github.com/mwouts/world_bank_data/blob/main/README.md), or our other [tutorial](https://github.com/mwouts/world_bank_data/blob/main/examples/) with the code required to produce this plot of the World Population:
+Go to our Binder and run either this [README](https://mybinder.org/v2/gh/mwouts/world_bank_data/main?labpath=README.md) or the notebook under `examples` to reproduce produce this plot of the World Population:
 
-[![World Population 2017](https://gist.githubusercontent.com/mwouts/ec3a88f1d97e36a062f69d4072b91e39/raw/79211a09957c6934fabf738a59c2c9b8df943696/world_population.gif)](https://nbviewer.jupyter.org/github/mwouts/world_bank_data/blob/main/examples/A%20sunburst%20plot%20of%20the%20world%20population.ipynb)
+[![World Population 2017](https://gist.githubusercontent.com/mwouts/ec3a88f1d97e36a062f69d4072b91e39/raw/79211a09957c6934fabf738a59c2c9b8df943696/world_population.gif)](https://mybinder.org/v2/gh/mwouts/world_bank_data/main?labpath=examples/A%20sunburst%20plot%20of%20the%20world%20population.py)
 
 # References
 

binder/labconfig/default_setting_overrides.json

@@ -0,0 +1,13 @@
+{
+  "@jupyterlab/docmanager-extension:plugin": {
+    "defaultViewers": {
+      "markdown": "Jupytext Notebook",
+      "myst": "Jupytext Notebook",
+      "r-markdown": "Jupytext Notebook",
+      "quarto": "Jupytext Notebook",
+      "julia": "Jupytext Notebook",
+      "python": "Jupytext Notebook",
+      "r": "Jupytext Notebook"
+    }
+  }
+}

binder/postBuild

@@ -1,9 +1,15 @@
-#!/bin/bash
-set -ex
+# Stop everything if one command fails
+set -e
 
-# Trust our notebooks
-jupyter trust examples/*.ipynb
+# Install from source
+pip install .
 
-# TOC extension
-jupyter contrib nbextension install --user
-jupyter nbextension enable toc2/main
+# Open text notebooks with the Notebook editor
+mkdir -p ${HOME}/.jupyter/labconfig
+cp binder/labconfig/* ${HOME}/.jupyter/labconfig
+
+# Install a kernel called world_bank_data
+python -m ipykernel install --name world_bank_data --user
+
+# Use that kernel for the README and the example notebooks
+jupytext README.md examples/* --set-kernel world_bank_data

binder/requirements.txt

@@ -1,4 +1,5 @@
-world_bank_data
-plotly>=3.8
+itables
+plotly
 jupytext
-jupyter_contrib_nbextensions
+jupyterlab_execute_time
+jupyter-resource-usage

examples/A sunburst plot of the world population.py

@@ -1,55 +1,49 @@
 # ---
 # jupyter:
 #   jupytext:
-#     formats: ipynb,py:light
+#     formats: ipynb,py:percent
 #     text_representation:
 #       extension: .py
-#       format_name: light
-#       format_version: '1.4'
-#       jupytext_version: 1.2.0-rc1
+#       format_name: percent
+#       format_version: '1.3'
+#       jupytext_version: 1.16.1
 #   kernelspec:
-#     display_name: Python 3
+#     display_name: Python 3 (ipykernel)
 #     language: python
 #     name: python3
 # ---
 
+# %% [markdown]
 # In this notebook we use the new Sunburst plot by [plotly](http://plot.ly/) to illustrate how the World population
 # is splitted among regions and countries. The data set illustrated here originates from the
 # [World Bank](https://data.worldbank.org). This notebook is also a quick demo for the
 # [world_bank_data](https://github.com/mwouts/world_bank_data/blob/main/README.md) Python package.
 
-# +
+# %%
 import pandas as pd
-import plotly
-import plotly.offline as offline
+import plotly.graph_objects as go
+from itables import init_notebook_mode
 
 import world_bank_data as wb
 
+init_notebook_mode(all_interactive=True)
 
-def version_to_int_list(version):
-    return [int(s) for s in version.split(".")]
-
-
-assert version_to_int_list(plotly.__version__) >= version_to_int_list(
-    "3.8.0"
-), "Sunburst plots require Plotly >= 3.8.0"
-
-pd.set_option("display.max_rows", 12)
-offline.init_notebook_mode()
-# -
-
+# %%
 # Countries and associated regions
 countries = wb.get_countries()
 countries
 
+# %%
 # Population dataset, by the World Bank (most recent value)
 population = wb.get_series("SP.POP.TOTL", mrv=1)
 population
 
+# %%
 # Same data set, indexed with the country code
 population = wb.get_series("SP.POP.TOTL", id_or_value="id", simplify_index=True, mrv=1)
 population
 
+# %%
 # Aggregate region, country and population
 df = (
     countries[["region", "name"]]
@@ -59,7 +53,7 @@ def version_to_int_list(version):
 df["population"] = population
 df
 
-# +
+# %%
 # The sunburst plot requires weights (values), labels, and parent (region, or World)
 # We build the corresponding table here
 columns = ["parents", "labels", "values"]
@@ -90,17 +84,14 @@ def version_to_int_list(version):
 
 all_levels = pd.concat([level1, level2, level3], axis=0).reset_index(drop=True)
 all_levels
-# -
 
+# %%
 # And now we can plot the World Population
-offline.iplot(
-    dict(
-        data=[dict(type="sunburst", hoverinfo="text", **all_levels)],
-        layout=dict(
-            title="World Population (World Bank, 2017)<br>Click on a region to zoom",
-            width=800,
-            height=800,
-        ),
+go.Figure(
+    data=[go.Sunburst(hoverinfo="text", **all_levels)],
+    layout=dict(
+        title="World Population (World Bank, 2017)<br>Click on a region to zoom",
+        width=800,
+        height=800,
     ),
-    validate=False,
 )