# Reading tabular data

### Read table data into R

```r
library("redivis")

# Specify the table's container, either a dataset or workflow
dataset <- redivis$organization("Demo")$dataset("iris_species")

table <- dataset$table("Iris")
table$to_tibble()
# 	Id	SepalLengthCm	SepalWidthCm	PetalLengthCm	PetalWidthCm	Species
# 0	33	5.2	        4.1	        1.5	        0.1	        Iris-setosa
# ...

# Other methods to read data:
# table$to_arrow_batch_reader()
# table$to_arrow_dataset()
# table$to_arrow_dataset()
# table$to_data_frame()
# table$to_data_table()
# table$to_sf_tibble()
```

### Read table metadata

```r
library("redivis")

table <- redivis$organization("Demo")$dataset("iris_species")$table("iris")

variable <- table$variable("sepalLengthCm")
variable$get() 

print(variable$properties)

{
  "kind": "variable",
  ... (see variable resource definition)
}

print(variable$get_statistics())
{
  "kind": "variableStatistics"
  "status": "completed",
  "count": 150,
  "numDistinct": 35,
  "min": 4.3,
  "max": 7.9,
  "mean": 5.8433333333333355,
  "approxMedian": 0.8280661279778625,
  ...
}
```

### Load a table within a Redivis notebook

<pre class="language-r"><code class="lang-r"><strong># In a notebook, all tables are scoped to the current workflow.
</strong># Additionally, the notebook's source table can simply be referenced as _source_
table = redivis$table("_source_")

table$to_tibble()
</code></pre>


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