data-coonverters: Typo fix: ee.date.computePixel → `ee.data.compute…

…Pixel`

PiperOrigin-RevId: 595715213

tutorials/data-converters/index.ipynb

@@ -47,7 +47,7 @@
         "\n",
         "Data converters are client-side conversion capabilities built into [`getPixels`](https://developers.google.com/earth-engine/apidocs/ee-data-getpixels), [`computePixels`](https://developers.google.com/earth-engine/apidocs/ee-data-computepixels), [`listFeatures`](https://developers.google.com/earth-engine/apidocs/ee-data-listfeatures), and [`computeFeatures`](https://developers.google.com/earth-engine/apidocs/ee-data-computefeatures). By specifying a compatible `fileFormat`, these methods can return data in Python-native formats like structured NumPy arrays for rasters and Pandas DataFrames or GeoPandas GeoDataFrames for vectors. In the case of vectors, the `listFeatures` and `computeFeatures` methods will make several network requests to fetch all the pages of the table before returning the Python object.\n",
         "\n",
-        "All of these methods transfer data from Earth Engine servers to a client machine using the [interactive processing environment](https://developers.google.com/earth-engine/guides/processing_environments#interactive_environment), which is optimized for answering small requests quickly. As such, it enforces limits on request size and compute time. You'll need to keep this in mind as you're coding your analysis and decide whether exporting data using the [batch processing environment](https://developers.google.com/earth-engine/guides/processing_environments#batch_environment) would be better. For example, see `ee.date.computePixel` limits in the [reference docs](https://developers.google.com/earth-engine/reference/rest/v1/projects.image/computePixels).\n",
+        "All of these methods transfer data from Earth Engine servers to a client machine using the [interactive processing environment](https://developers.google.com/earth-engine/guides/processing_environments#interactive_environment), which is optimized for answering small requests quickly. As such, it enforces limits on request size and compute time. You'll need to keep this in mind as you're coding your analysis and decide whether exporting data using the [batch processing environment](https://developers.google.com/earth-engine/guides/processing_environments#batch_environment) would be better. For example, see `ee.data.computePixel` limits in the [reference docs](https://developers.google.com/earth-engine/reference/rest/v1/projects.image/computePixels).\n",
         "\n",
         "Some common use cases for data converters are fetching many small image tiles in parallel (e.g., training ML models or automated serial workflows) and for visualization and data exploration with your favorite Python libraries. This notebook focuses on data exploration and visualization; if you're interested in learning about fetching data in parallel, see the Medium blog post \"[Pixels to the people!](https://medium.com/google-earth/pixels-to-the-people-2d3c14a46da6)\"."
       ],