# Calculating median and quantiles#

```
# import core as core
from iosacal import R
```

This notebook demonstrates how to compute a calibrated median and 68 or 95% confidence interval from a radiocarbon datum.1

```
#example radiocarbon
c14_ages = [2000, 3000, 4500, 6500]
c14_1σ = [300, 260, 50, 70]
for age, oneσ in zip(c14_ages, c14_1σ):
cr = R(age, oneσ, 'test')
cal = cr.calibrate('intcal20')
quants = cal.quantiles()
print(f'\n Median = {quants[50]} \n 1σ = {quants[68]} \n 2σ = {quants[95]} ')
```

```
Median = 1969.0
1σ = [1611.0, 2330.0]
2σ = [1355.0, 2710.0]
```

```
Median = 3171.0
1σ = [2854.0, 3453.0]
2σ = [2494.0, 3834.0]
Median = 5155.0
1σ = [5052.0, 5287.0]
2σ = [4976.0, 5312.0]
Median = 7395.0
1σ = [7324.0, 7474.0]
2σ = [7273.0, 7562.0]
```

- 1
This notebook can be downloaded as

`quantiles_demo.ipynb`