# Pull data for a single node

Fetch day-ahead hourly settlement point prices for a specific ERCOT node.

```python
# Get day-ahead hourly prices for HB_NORTH node
df = client.get_dataset(
    "ercot_spp_day_ahead_hourly",
    start="2026-01-01",
    end="2026-01-08",
    filter_column="location",
    filter_value="HB_NORTH"
)

print(f"Retrieved {len(df)} rows for HB_NORTH")
print(f"\nDate range: {df['interval_start_utc'].min()} to {df['interval_start_utc'].max()}")
print(f"\nPrice statistics:")
print(f"  Mean: ${df['spp'].mean():.2f}/MWh")
print(f"  Max: ${df['spp'].max():.2f}/MWh")
print(f"  Min: ${df['spp'].min():.2f}/MWh")

# Display first few rows
print(f"\nFirst 5 rows:")
print(df.head())
```

You can also omit the `end` parameter to automatically fetch data up to the latest available:

```python
from datetime import datetime

# Get all available data from today (rounded down) through the latest available
df = client.get_dataset(
    "ercot_spp_day_ahead_hourly",
    start=datetime.now().date(),
    filter_column="location",
    filter_value="HB_NORTH"
)

print(f"Retrieved {len(df)} rows for HB_NORTH")
print(f"\nDate range: {df['interval_start_utc'].min()} to {df['interval_start_utc'].max()}")
print(f"\nMost recent price: ${df['spp'].iloc[-1]:.2f}/MWh")
```


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