Testing writing a post from scratch.

The goals of this test are the following:

Can I connect to GCP/BigQuery to pull data into the notebook? Yes
How does the formatting look once published? Is it acceptable? Yes, and you can hide sensitive code
What happens if there are open comments on the notebook when published? Do they show? They remain in Deepnotes, but don't show in the blog post.
How can I more effectively save a post here and publish to the appropriate file location on GitHub for Fastpages? Can I save directly? And does the publishing action on GitHub fire automatically? Deepnote can sync with GitHub. Additional folders/files not in the Fastpages file schema don't seem to be able to be puhed. The GitHub Actions fire automatically to update the posts.

df_1 = _deepnote_execute_sql("""#hide_input

select election_cycle, sum(dem_predicted)
from `nyu-cap-ae.final.tableau_final_market`
group by 1
limit 100;
""", 'SQL_A68E38DE_5115_4DF4_BA9E_46073050F7D2')
df_1

There is supposed to be a built in visualization that shows below, but it doesn't work with Fastpages. Could be useful for quick and dirty adhoc visualizations in Deepnote while exploring data though.

_deepnote_run_altair(df_1, """{"$schema":"https://vega.github.io/schema/vega-lite/v4.json","mark":{"type":"bar","tooltip":{"content":"data"}},"height":220,"autosize":{"type":"fit"},"data":{"name":"placeholder"},"encoding":{"x":{"field":"election_cycle","type":"nominal","sort":null,"scale":{"type":"linear","zero":false}},"y":{"field":"f0_","type":"quantitative","sort":null,"scale":{"type":"linear","zero":true}},"color":{"field":"f0_","type":"quantitative","sort":null,"scale":{"type":"linear","zero":false}}}}""")

Unfortunately, it doesn't work because fastpages doesn't recognize this command:

_deepnote_run_altair(df_1, """{"$schema":"https://vega.github.io/schema/vega-lite/v4.json","mark":{"type":"bar","tooltip":{"content":"data"}},"height":220,"autosize":{"type":"fit"},"data":{"name":"placeholder"},"encoding":{"x":{"field":"election_cycle","type":"nominal","sort":null,"scale":{"type":"linear","zero":false}},"y":{"field":"f0_","type":"quantitative","sort":null,"scale":{"type":"linear","zero":true}},"color":{"field":"f0_","type":"quantitative","sort":null,"scale":{"type":"linear","zero":false}}}}""")

Since that doesn't work, let's try using matplotlib

import matplotlib.pyplot as plt; plt.rcdefaults()
import numpy as np
import matplotlib.pyplot as plt

objects = ('Python', 'C++', 'Java', 'Perl', 'Scala', 'Lisp')
y_pos = np.arange(len(objects))
performance = [10,8,6,4,2,1]

plt.bar(y_pos, performance, align='center', alpha=0.5)
plt.xticks(y_pos, objects)
plt.ylabel('Usage')
plt.title('Programming language usage')

plt.show()

Yay, now it works!

</img> Created in Deepnote

	election_cycle	f0_
0	2018	2348452.0
1	2020	2152852.0
2	2016	1833835.0
3	2022	3461406.0