actuarialopensource / actuarialopensource/benchmarks

Presentation of output

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Description

I think the first table like this facilitates comparison more so than the latte:

```
Times are in nanoseconds:
┌──────────┬──────────────────┬───────────────────┬─────────┬─────────────┬───────────────┐
│ Language │ Package │ Function │ Median │ Mean │ Relative Mean │
├──────────┼──────────────────┼───────────────────┼─────────┼─────────────┼───────────────┤
│ Python │ numpy_financial │ irr │ missing │ 5339167688 │ 332824x │
│ Python │ better │ irr_binary_search │ missing │ 6167798 │ 384x │
│ Python │ better │ irr_newton │ missing │ 945813 │ 59x │
│ Julia │ ActuaryUtilities │ irr │ 16000 │ 16042 │ 1x │
└──────────┴──────────────────┴───────────────────┴─────────┴─────────────┴───────────────┘
```

vs
```
basic_term_benchmark:
- Julia CacheFlow basic_term:
mean: TrialEstimate(192.127 ms)
result: 1.4489630534602132e7
- Python jax basic_term_m:
mean: 337.39129650000166 milliseconds
result: 14489630.53460337
Python lifelib basic_term_m:
mean: 1182.7541804499986 milliseconds
result: 14489630.534601536
Python scratch basic_term_m:
mean: 957.6274868500008 milliseconds
result: 14489630.534603368
```

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