update

README.md

@@ -26,9 +26,7 @@ As the underlying `zarr`, the `dataset` is an iterable:
 ```python
 from ecml_tools.data import open_dataset
 
-ds = open_dataset(
-    "aifs-ea-an-oper-0001-mars-o96-1979-2022-1h-v2",
-)
+ds = open_dataset("aifs-ea-an-oper-0001-mars-o96-1979-2022-1h-v2")
 
 # Print the number of rows (i.e. dates):
 
@@ -58,22 +56,26 @@ row = ds[10]
 print("2t", row[two_t_index])
 
 # Get the list of dates (as NumPy datetime64)
+
 print(ds.dates)
 
 # The number of hours between consecutive dates
+
 print(ds.frequency)
 
 # The resolution of the underlying grid
 
 print(ds.resolution)
 
 # The list of latitudes of the data values (NumPy array)
+
 print(ds.latitudes)
 
 # The same for longitudes
+
 print(ds.longitudes)
 
-# The statitics
+# And the statitics
 
 print(ds.statistics)
 
@@ -98,8 +100,6 @@ stats = ds.statistics
 print("Average 2t", stats["mean"][two_t_index])
 ```
 
-
-
 ## Subsetting datasets
 
 You can create a view on the `zarr` file that selects a subset of dates.
@@ -147,7 +147,6 @@ training = open_dataset("aifs-ea-an-oper-0001-mars-o96-1979-2022-1h-v2",
     frequency="6h")
 ```
 
-
 ## Combining datasets
 
 You can create a virtual dataset by combining two or more `zarr` files.
@@ -164,7 +163,6 @@ ds = open_dataset(
 
 ```
 
-
 When given a list of `zarr` files, the package will automatically work out if the files can be _concatenated_ or _joined_ by looking at the range of dates covered by each files.
 
 If the dates are different, the files are concatenated. If the dates are the same, the files are joined. See below for more information.