Edit README

README.md

@@ -1,4 +1,4 @@
-# Introduction to Scientific Computing course  
+# Introduction to Scientific Computing course
 This repository holds teaching materials for the NCAS Introduction to Scientific Computing course.  
 
 ## Overview  
@@ -12,14 +12,11 @@ The course covers:
   - [Presentation](https://github.com/ncasuk/ncas-isc/tree/main/version_control)  
   - [Exercise](https://github.com/ncasuk/ncas-isc/tree/main/version_control)
 - Introduction to Python
-  - [Python Introduction Slides](https://github.com/ncasuk/ncas-isc/blob/main/python-intro/presentations.md) 
+  - [Python Introduction Slides](https://github.com/ncasuk/ncas-isc/blob/main/python-intro/README.md) 
   - [Exercises - Jupyter Notebooks](https://github.com/ncasuk/ncas-isc/tree/main/python-intro/exercises) | [Solutions](https://github.com/ncasuk/ncas-isc/tree/main/python-intro/solutions) 
 - Data manipulation and visualisation in Python (Working with Data)
-  - [Python working with data Slides](https://github.com/ncasuk/ncas-isc/tree/main/python-data/slides) 
-  - [Exercises - Jupyter Notebooks](https://github.com/ncasuk/ncas-isc/tree/main/python-data/notebooks) | [Solutions](https://github.com/ncasuk/ncas-isc/tree/main/python-data/solutions)
-- Example code for all python modules
-  - [Example code for Python (Working with Data)](https://github.com/ncasuk/ncas-isc/tree/main/python-data/example_code)
-  - [Example data for Python (Working with Data)](https://github.com/ncasuk/ncas-isc/tree/main/python-data/example_data)
+  - [Python working with data Slides](https://github.com/ncasuk/ncas-isc/tree/main/python-data/README.md) 
+  - [Exercises - Jupyter Notebooks](https://github.com/ncasuk/ncas-isc/tree/main/python-data/exercises) | [Solutions](https://github.com/ncasuk/ncas-isc/tree/main/python-data/solutions)
 
 ## Index  
 ### Overview Presentations  
@@ -57,9 +54,11 @@ The course covers:
 
 ## Python - Working with Data
 
-### Handling arrays  
-* [Numpy](https://github.com/ncasuk/ncas-isc/blob/main/python-data/slides/numpy.pdf)  
-* [Exercises](https://github.com/ncasuk/ncas-isc/blob/main/python-data/notebooks/ex01_numpy_arrays.ipynb) and [Solutions](https://github.com/ncasuk/ncas-isc/blob/main/python-data/solutions/ex01_numpy_arrays_solutions.ipynb)
+### xarray
+| Lesson | Exercise | Solution |
+| ------ | -------- | -------- |
+| [Intro to multidimensional arrays](https://geohackweek.github.io/nDarrays/01-introduction/), [xarray](https://geohackweek.github.io/nDarrays/02-xarray-architecture/) and [indexing](https://geohackweek.github.io/nDarrays/03-label-based-indexing/) | [Exercise 01]() | [Solution 01]() |
+
 
 ### Visualisation  
 * [Matplotlib and cartopy](https://github.com/ncasuk/ncas-isc/blob/main/python-data/slides/matplotlib_and_cartopy.pdf)  

python-data/solutions/ex01_xarray_intro.ipynb

@@ -72,7 +72,7 @@
    "id": "48d19019-2546-46d3-9da1-64d8e7c363e8",
    "metadata": {},
    "source": [
-    "1. Open the test dataset '' and load it into an xarray `Dataset` called `ds`.\n",
+    "1. Open the `'../data/tas_rcp45_2055_mon_avg_change.nc'` dataset and load it into an xarray `Dataset` called `ds`.\n",
     "(Hint: Don't forget to import any packages you need)"
    ]
   },
@@ -574,7 +574,7 @@
    "id": "3cee6429-dbf8-4a10-b384-ad9de719a0d0",
    "metadata": {},
    "source": [
-    "What are the dimensions and variables in this dataset? What does each represent? "
+    "3. What are the dimensions and variables in this dataset? What does each represent? "
    ]
   },
   {
@@ -593,7 +593,7 @@
    "id": "81207a17-eeaf-4de3-a3f6-9a0fd782c252",
    "metadata": {},
    "source": [
-    "3. Find the name of the Data Variable, and use it to extract a `DataArray` called `temperature`."
+    "4. Find the name of the Data Variable, and use it to extract a `DataArray` called `temperature`."
    ]
   },
   {
@@ -612,7 +612,7 @@
    "id": "6ee4a984-305e-44da-87ab-75cf88d71f22",
    "metadata": {},
    "source": [
-    "4. Take a look at the `temperature` data array and inspect its dimensions, coordinates and attributes. What are the specific dimensions and coordinates associated with it? What metadata (attributes) is provided?"
+    "5. Take a look at the `temperature` data array and inspect its dimensions, coordinates and attributes. What are the specific dimensions and coordinates associated with it? What metadata (attributes) is provided?"
    ]
   },
   {
@@ -1083,7 +1083,7 @@
    "id": "f3e16f51-8a98-424a-b908-87360947f69a",
    "metadata": {},
    "source": [
-    "5. Select a subset of the `temperature` array using label-based indexing to get data at the position [0,0,0]."
+    "6. Select a subset of the `temperature` array using label-based indexing to get data at the position [0,0,0]."
    ]
   },
   {
@@ -1507,7 +1507,7 @@
    "id": "2545ea6f-ad6c-4612-86c4-95cc9d23ffdb",
    "metadata": {},
    "source": [
-    "6. Use `.loc` to find the lat and lon values at the time `2065-01-30`. "
+    "7. Use `.loc` to find the lat and lon values at the time `2065-01-30`. "
    ]
   },
   {
@@ -1955,7 +1955,7 @@
    "id": "61407fc5-2ff3-4467-875d-f3e3b06eaa34",
    "metadata": {},
    "source": [
-    "6. It's not ideal to have to keep track of which dimension is in which position. Instead, use `.isel` to use the dimension names to get the data in the first time, lat and lon position."
+    "8. It's not ideal to have to keep track of which dimension is in which position. Instead, use `.isel` to use the dimension names to get the data in the first time, lat and lon position."
    ]
   },
   {
@@ -2379,7 +2379,7 @@
    "id": "0f6f10a7-0905-42ec-9bf4-b3cf07229637",
    "metadata": {},
    "source": [
-    "8. The previous method is still referring to a selection by integer position. Use `.sel` to give a labelled index with the named dimension to find the data at `time=2065-12-30`, `lat=-78.5`, `lon=11.0`."
+    "9. The previous method is still referring to a selection by integer position. Use `.sel` to give a labelled index with the named dimension to find the data at `time=2065-12-30`, `lat=-78.5`, `lon=11.0`."
    ]
   },
   {