Hey! Scaling variables to unit interval python is something I’ve struggled with too, especially with edge cases. MinMaxScaler is great, but sometimes I prefer writing my own function for more control.
Here’s a quick snippet:
```python
def scale_to_unit(data):
min_val = np.min(data)
max_val = np.max(data)
if min_val == max_val:
return np.zeros_like(data)
return (data - min_val) / (max_val - min_val)
```
For large datasets, numpy is usually fast enough, but if you’re working with REALLY big data, consider using Dask or PySpark. They’re built for scaling variables to unit interval python at scale.
Here’s a quick snippet:
```python
def scale_to_unit(data):
min_val = np.min(data)
max_val = np.max(data)
if min_val == max_val:
return np.zeros_like(data)
return (data - min_val) / (max_val - min_val)
```
For large datasets, numpy is usually fast enough, but if you’re working with REALLY big data, consider using Dask or PySpark. They’re built for scaling variables to unit interval python at scale.
