import pandas as pd
download dataset via Open Science Framework
df = pd.read_csv(
'https://osf.io/vcfa9/download',
compression='xz',
)
# run me to see a formatted preview of the dataset
df
Series | Mean Inter-Strain Fitness Differential | Fraction Inter-Strain Competitions Won | Inter-Strain Competition Null p-value | Flagged Advantageous Sites | Flagged Deleterious Sites | H_0 Advantageous Site Flags | H_0 Deleterious Site Flags | Estimated True Advantageous Sites | Estimated True Deleterious Sites | ... | Resource Receiving Cardinal Fraction | Resource Receiving Cell Fraction | Resource Reserve Request Cardinal Fraction | Resource Reserve Request Cell Fraction | Resource Send Request Cardinal Fraction | Resource Send Request Cell Fraction | Spawn Arrest Cardinal Fraction | Spawn Arrest Cell Fraction | Spawn Request Cardinal Fraction | Spawn Request Cell Fraction | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 11000 | -0.000025 | 0.45 | 0.823803 | 11 | 0 | 0.51 | 0.51 | 10.49 | -0.51 | ... | 0.003760 | 0.015040 | 0.484576 | 0.782075 | 0.246931 | 0.504604 | 0.012201 | 0.048189 | 0.352594 | 0.707489 |
1 | 11001 | -0.000033 | 0.50 | 1.000000 | 10 | 2 | 0.29 | 0.29 | 9.71 | 1.71 | ... | 0.003528 | 0.014113 | 0.013525 | 0.052926 | 0.013893 | 0.054690 | 0.013672 | 0.054102 | 0.295354 | 0.683916 |
2 | 11002 | -0.000204 | 0.30 | 0.115318 | 2 | 0 | 0.06 | 0.06 | 1.94 | -0.06 | ... | 0.002575 | 0.010302 | 0.013588 | 0.053996 | 0.012877 | 0.051510 | 0.010391 | 0.041208 | 0.326021 | 0.716874 |
3 | 11003 | 0.000937 | 0.95 | 0.000040 | 10 | 3 | 0.36 | 0.36 | 9.64 | 2.64 | ... | 0.001707 | 0.006830 | 0.319650 | 0.557484 | 0.013588 | 0.053216 | 0.015723 | 0.061468 | 0.075911 | 0.195788 |
4 | 11004 | -0.000102 | 0.50 | 1.000000 | 9 | 0 | 0.11 | 0.11 | 8.89 | -0.11 | ... | 0.002780 | 0.011122 | 0.012552 | 0.047982 | 0.013267 | 0.051478 | 0.108119 | 0.253575 | 0.543772 | 0.865269 |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
75 | 11035 | 0.000037 | 0.70 | 0.115318 | 13 | 0 | 0.74 | 0.74 | 12.26 | -0.74 | ... | 0.029764 | 0.116396 | 0.014993 | 0.058493 | 0.013146 | 0.051403 | 0.014328 | 0.055835 | 0.440177 | 0.745938 |
76 | 11036 | -0.000106 | 0.40 | 0.503445 | 8 | 0 | 0.85 | 0.85 | 7.15 | -0.85 | ... | 0.036085 | 0.139590 | 0.073136 | 0.156222 | 0.013068 | 0.050787 | 0.486932 | 0.894268 | 0.390852 | 0.679537 |
77 | 11037 | -0.000205 | 0.10 | 0.000402 | 11 | 0 | 0.48 | 0.48 | 10.52 | -0.48 | ... | 0.003910 | 0.015639 | 0.216731 | 0.597226 | 0.014016 | 0.055769 | 0.002508 | 0.010032 | 0.295958 | 0.651815 |
78 | 11038 | -0.000061 | 0.50 | 1.000000 | 10 | 1 | 0.43 | 0.43 | 9.57 | 0.57 | ... | 0.058918 | 0.220250 | 0.998545 | 0.999709 | 0.015130 | 0.059354 | 0.925007 | 0.999709 | 0.997090 | 0.999709 |
79 | 11039 | -0.000064 | 0.60 | 0.503445 | 7 | 0 | 0.69 | 0.69 | 6.31 | -0.69 | ... | 0.001653 | 0.006613 | 0.019312 | 0.075443 | 0.013375 | 0.052600 | 0.098137 | 0.222122 | 0.106102 | 0.306583 |
80 rows × 242 columns
add your own analyses below!