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(f_rs_edit)=


----------------

```{admonition} Learning Objectives
- Handle missing values
- Setting missing values
- Replacing values

```
```{admonition} Review
* [Opening remotely sensed data](f_rs_io.md)
```
----------------

# Editing Rasters and Remotely Sensed Data


## Masking Out Certain Values

The `xarray.DataArray.where` function masks data by setting nans, as demonstrated by the example below.

```{code-cell} ipython3
import geowombat as gw
from geowombat.data import l8_224078_20200518

# Zeros are replaced with nans
with gw.open(l8_224078_20200518) as src:
    data = src.where(src != 0)
```

## Setting 'no data' Values  
Setting missing data values, when not available in the raster profile, can be done using the [configuration manager](f_rs_config.md) or as an argument in the `open` command. 

```{code-cell} ipython3
import geowombat as gw
from geowombat.data import l8_224078_20200518

# Zeros are replaced with nans
with gw.open(l8_224078_20200518, nodata=0) as src:
    print('gw.open: ',src.attrs['nodatavals'])
    #  replace 0 with nan
    src=src.gw.mask_nodata() 


# Zeros are replaced with nans
with gw.config.update(nodata=0):
  with gw.open(l8_224078_20200518) as src:
    print('gw.config',src.attrs['nodatavals'])
    #  replace 0 with nan
    src=src.gw.mask_nodata() 
```

## Rescaling Values 
Most remotely sensed data is stored as `int` to minimize space. We are often left to rescale the values back to floating point on the backend. This can be done in a few ways in geowombat. If the sensor you are using has a geowombat profile, please use that - refer to [configuration manager docs](f_rs_config.md). If it is not natively supported we can manually set the scaling factor using the `gw.config.update`


```{code-cell} ipython3
import geowombat as gw
from geowombat.data import l8_224078_20200518
 
# Zeros are replaced with nans
with gw.config.update(scale_factor=0.0001):
  with gw.open(l8_224078_20200518) as src:
    print(src.gw.scale_factor)
```
 
## Replace values

The GeoWombat `replace` function mimics `pandas.DataFrame.replace`.

```{code-cell} ipython3
import geowombat as gw
from geowombat.data import l8_224078_20200518

# Replace 1 with 10
with gw.open(l8_224078_20200518) as src:
    data = src.gw.replace({1: 10})
```

```{note}    
The `replace` function is typically used with categorical data.
```

## Updating Values

Geowombat also accepts normal mathematical expressions such as multiplication and addition:

```{code-cell} ipython3
import geowombat as gw
from geowombat.data import l8_224078_20200518

# Replace 1 with 10
with gw.open(l8_224078_20200518) as src:
    data = src * 0.001 +80
    print(data[0].values)
```