annopath <- path_1kg_annotations()
tab <- hl$import_table(annopath, impute=TRUE)$key_by("Sample")
```
```{python ch3, eval=TRUE}
r.tab.describe()# python chunk!
r.tab.show(width=100)
```

## Adding the sample annotation to the MatrixTable; aggregation

We combine the `tab` defined above, with the MatrixTable instance,
usiny python code reaching to R via `r.`.
```{python ch4, eval=TRUE}
r.mt = r.mt.annotate_cols(pheno = r.tab[r.mt.s])   # python chunk!
r.mt.col.describe()
```

Aggregation methods can be used to obtain contingency tables or descriptive statistics.

First, we get the frequencies of superpopulation membership:
```{r getsup, eval=TRUE}
mt$aggregate_cols(hl$agg$counter(mt$pheno$SuperPopulation))

