Marco Edward Gorelli MarcoGorelli

✊

raise the alarm, climate emergency!

MarcoGorelli / block1.bash

Created June 28, 2020 11:35

$ jupyter nbconvert notebooks/hello_world.ipynb --output-dir build

MarcoGorelli / block2.bash

Created June 28, 2020 11:35

$ jupyter nbconvert notebooks/fibonacci_plot.ipynb --output-dir build --no-input

MarcoGorelli / block3.python

Created June 28, 2020 11:35

	# source: https://stackoverflow.com/a/28073228/9988333

	from IPython.display import HTML

	HTML(
	"""<script>
	code_show=true;
	function code_toggle() {
	if (code_show){
	$('div.input').hide();

MarcoGorelli / block4.bash

Last active February 11, 2021 15:56

	$ jupyter nbconvert notebooks/fibonacci_plot.ipynb \
	--TagRemovePreprocessor.enabled=True \
	--TagRemovePreprocessor.remove_input_tags "remove-input" \
	--TagRemovePreprocessor.remove_all_outputs_tags "remove-output" \
	--no-prompt \
	--output-dir build \
	--template classic \
	--to html

MarcoGorelli / check_python_script.sh

Last active August 2, 2020 08:31

flake8 my_script.py

MarcoGorelli / check_notebook

Created August 2, 2020 08:32

nbqa flake8 my_notebook.ipynb

MarcoGorelli / .pre-commit-config.yaml

Last active June 3, 2021 07:12

pre-commit example

	- repo: https://github.com/nbQA-dev/nbQA
	rev: 0.10.0
	hooks:
	- id: nbqa-flake8
	- id: nbqa-isort
	- id: nbqa-mypy
	- id: nbqa-black

MarcoGorelli / install requests

Created August 9, 2020 17:45

pip install requests

MarcoGorelli / get_stats.py

Created August 9, 2020 17:55

	import requests
	import os

	data = requests.get('https://api.github.com/search/issues?q=is:pr+repo:pandas-dev/pandas+author:marcogorelli+is:merged').json()

	print(f"Merged PRs: {data['total_count']}")

	url = 'https://api.github.com/graphql'
	query = (
	"""

MarcoGorelli / coin_tossing.py

Last active August 30, 2020 10:58

coin_tossing

	import arviz as az
	import pymc3 as pm

	N = 1000
	N_HEADS = 292

	with pm.Model() as model:
	theta = pm.Beta("θ", alpha=1.0, beta=1.0)
	y = pm.Binomial("y", n=N, p=theta, observed=N_HEADS)
	trace = pm.sample(return_inferencedata=True)