> ## Documentation Index
> Fetch the complete documentation index at: https://knowledge.cloudquant.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Usage of the back_to Parameter

> How to use the back_to parameter to define the start of a time range in CloudQuant Data Liberator queries.

# Usage of the back\_to parameter

The `back_to` parameter is a datetime parameter in CloudQuant Data Liberator queries that defines the start point of a time range for data retrieval.

## Parameter format

You can specify `back_to` in two ways:

**Date only:**

```
'2024-07-08'
```

CloudQuant Data Liberator interprets this as midnight: `'2024-07-08 00:00:00.000000'`

**Specific time:**
You can set it to any time down to nanosecond precision.

## Important notes

<Info>
  All CloudQuant Data Liberator times are New York Time (US ET).
</Info>

<Warning>
  Start with small queries to understand data amounts before requesting large date ranges.
</Warning>

* If `back_to` is omitted or set to `None`, CloudQuant Data Liberator returns the most recent value at the specified `as_of` time.

## Default behavior example

Without `back_to`, the query returns the latest available data:

```python theme={null}
df = liberator.get_dataframe(liberator.query(
    name = 'daily_bars',
    as_of = '2023-12-25',
    symbols = ['GOOG', 'AAPL', 'MSFT']
))
```

Since December 25, 2023 was not a trading day, CloudQuant Data Liberator returned data from the most recent trading day (December 22, 2023).