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# Reading CSV DataFrame
Go to **New Reservoir Release** node and change **Max Flow** to **-400**, this will allow to flow water through this node
The downloaded file, **Thames\_Lee\_Valley\_demand.csv**, contains a time series dataset structured with two key columns:
**timestep:** This column will serve as the index for the time series. It represents the progression of time in the dataset, allowing for chronological organization.
**Lee Valley Demand:** This column contains the data representing demand values in the Lee Valley.
Thames_Lee_Valley_demand
Select the output node **Lee Valley Demand** and Edit the **Max Flow**
In Options select **PYWR\_PARAMETER**
Paste the following configuration:
```json
{
"type": "DataFrameParameter",
"url": "Thames_Lee_Valley_demand.csv",
"column": "Lee Valley Demand",
"index_col": "timestep",
"parse_dates": true
}
```
Now it should look as the following image:
### Results
Click on node Lee Valley Demand > Outputs > simulated\_flow to see results of the simulation
simulated_flow (Lee Valley Demand)
Now check the **simulated\_volume** for **New reservoir**
simulated volume (New Reservoir)
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