| import ipywidgets as widgets | |
| import random | |
| max_secret = 10 | |
| secret = random.randint(1, max_secret) | |
| guesses_allowed = 3 | |
| guesses_made = 0 | |
| game_still_going = True | |
| # to leave out the quotes around strings sent to `ouptut.update()`, based on https://stackoverflow.com/a/70130979/8508004 |
Benefits:
The code below scans an .ipynb file where the first two and fifth cells were run (named example_nb_saved_first_two_cells_run_plus_last.ipynb) and then makes a new notebook out of the executed cells:
import nbformat as nbf
ntbk = nbf.read("example_nb_saved_first_two_cells_run_plus_last.ipynb", nbf.NO_CONVERT)
cells_executed_previously = []
for cell in ntbk.cells:
if cell.execution_count != None:
cells_executed_previously.append(cell)
new_ntbk = ntbk
In general, I opt for Seaborn when plotting with Python. It is built on top of Matplotlib and handles a lot of the style stuff better than default Matplotlib.
A good initial starting point to getting it close to Excel is to use Seaborn's 'whitegrid' that you set with Seaborn's set_style() method.
So to kick things off, it is common to do:
import seaborn as sns
import matplotlib.pyplot as plt
millefy-binder pre-converted BigWig files from package-supplied BAM files.
Millefy came with BAM files in /srv/conda/envs/notebook/lib/R/library/millefy/extdata/bam. Here they have been converted to BigWig format using deepTools' bamCoverage.
binSize here is 15. Running this on MyBinder would take a long time. So this is to allow it not to take as long as it should.