Add 95% CI error bars to CE and CW examples (Sourcery refactored)

[sourcery-ai]

Pull Request #14 refactored by Sourcery.

If you're happy with these changes, merge this Pull Request using the Squash and merge strategy.

NOTE: As code is pushed to the original Pull Request, Sourcery will
re-run and update (force-push) this Pull Request with new refactorings as
necessary. If Sourcery finds no refactorings at any point, this Pull Request
will be closed automatically.

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To manually merge these changes, make sure you're on the error_bars branch, then run:

git fetch origin sourcery/error_bars
git merge --ff-only FETCH_HEAD
git reset HEAD^

Help us improve this pull request!

[sourcery-ai]

Lines 97-97 refactored with the following changes:

• Replace unused for index with underscore (for-index-underscore)

[sourcery-ai]

Lines 54-132 refactored with the following changes:

• Merge consecutive list appends into a single extend (merge-list-appends-into-extend)
• Replace unused for index with underscore (for-index-underscore)

This removes the following comments ( why? ):

# Likelihood of Condorcet Winner (normalized by n iterations)

[sourcery-ai]

Function func refactored with the following changes:

• Replace unused for index with underscore (for-index-underscore)

[sourcery-ai]

Lines 64-64 refactored with the following changes:

• Replace unused for index with underscore (for-index-underscore)

[sourcery-ai]

Sourcery Code Quality Report

✅  Merging this PR will increase code quality in the affected files by 0.08%.

Quality metrics	Before	After	Change
Complexity	26.30 😞	26.28 😞	-0.02 👍
Method Length	376.60 ⛔	375.80 ⛔	-0.80 👍
Working memory	21.03 ⛔	21.01 ⛔	-0.02 👍
Quality	24.28% ⛔	24.36% ⛔	0.08% 👍

Other metrics	Before	After	Change
Lines	389	393	4

Changed files	Quality Before	Quality After	Quality Change
examples/merrill_1984_fig_2c_2d.py	7.09% ⛔	7.09% ⛔	0.00%
examples/merrill_1984_table_1_fig_1.py	13.13% ⛔	13.13% ⛔	0.00%
examples/wikipedia_condorcet_paradox_likelihood.py	71.17% 🙂	71.17% 🙂	0.00%

Here are some functions in these files that still need a tune-up:

File	Function	Complexity	Length	Working Memory	Quality	Recommendation

Legend and Explanation

The emojis denote the absolute quality of the code:

• ⭐ excellent
• 🙂 good
• 😞 poor
• ⛔ very poor

The 👍 and 👎 indicate whether the quality has improved or gotten worse with this pull request.

---

Please see our documentation here for details on how these metrics are calculated.

We are actively working on this report - lots more documentation and extra metrics to come!

Help us improve this quality report!

[endolith]

meh.