Merge pull request #38 from ProjectPythia/jukent

Fix foundations links

Author: jukent

README.md

@@ -57,7 +57,7 @@ and even change the example programs. You’ll see that the code cells
 have no output at first, until you execute them by pressing
 {kbd}`Shift`\+{kbd}`Enter`. Complete details on how to interact with
 a live Jupyter notebook are described in [Getting Started with
-Jupyter](https://foundations.projectpythia.org/foundations/getting-started-jupyter.html).
+Jupyter](https://foundations.projectpythia.org/foundations/getting-started-jupyter).
 
 ### Running on Your Own Machine
 If you are interested in running this material locally on your computer, you will need to follow this workflow:

notebooks/creating_catalogs.ipynb

@@ -44,8 +44,8 @@
     "| --- | --- | --- |\n",
     "| [Intro to Intake](./intake_introduction.ipynb) | Necessary | |\n",
     "| [Understanding of yaml](https://yaml.org/spec/1.2.2/#chapter-1-introduction-to-yaml) | Necessary |  |\n",
-    "| [Getting Started with Github](https://foundations.projectpythia.org/foundations/getting-started-github.html) | Necessary | |\n",
-    "| [Intro to Pandas](https://foundations.projectpythia.org/core/pandas/pandas.html) | Helpful | |\n",
+    "| [Getting Started with Github](https://foundations.projectpythia.org/foundations/getting-started-github) | Necessary | |\n",
+    "| [Intro to Pandas](https://foundations.projectpythia.org/core/pandas/pandas) | Helpful | |\n",
     "\n",
     "\n",
     "- **Time to learn**: 45 minutes"
@@ -139,7 +139,7 @@
    "metadata": {},
    "source": [
     "## Adding Your First Data Source\n",
-    "Intake only knows how to handle a few different data formats. To handle other formats it uses plugable drivers. To use the [Mesowest's HRRR Zarr data](https://mesowest.utah.edu/html/hrrr/) we will use the intake-xarray package which provides a driver for reading Zarr data into [Xarray](https://foundations.projectpythia.org/core/xarray.html) datasets. Drivers are installed as python packages and integrate into the Intake library. When intalled Intake creates a open_{driver} method for each driver in the package. Installing the intake-xarray package allows us to access zarr data using the `open_zarr` method.\n",
+    "Intake only knows how to handle a few different data formats. To handle other formats it uses plugable drivers. To use the [Mesowest's HRRR Zarr data](https://mesowest.utah.edu/html/hrrr/) we will use the intake-xarray package which provides a driver for reading Zarr data into [Xarray](https://foundations.projectpythia.org/core/xarray) datasets. Drivers are installed as python packages and integrate into the Intake library. When intalled Intake creates a open_{driver} method for each driver in the package. Installing the intake-xarray package allows us to access zarr data using the `open_zarr` method.\n",
     "\n",
     "Mesowest's HRRR Zarr data is stored in AWS. The [file structure](https://mesowest.utah.edu/html/hrrr/zarr_documentation/html/zarr_variables.html) of the [hrrrzarr S3 bucket](https://hrrrzarr.s3.amazonaws.com/index.html) looks like \n",
     "\n",
@@ -185,7 +185,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Above we used the `storage_options` argument to tell Intake how to access data on AWS. In this case we accessed the data as an anonymous user. The `consolidated=True` argument is given to tell [Xarray](https://foundations.projectpythia.org/core/xarray.html) how to load the metadata for this source. Zarr data may contain consolidated metadata. If it does, using it can increase performance significantly.\n",
+    "Above we used the `storage_options` argument to tell Intake how to access data on AWS. In this case we accessed the data as an anonymous user. The `consolidated=True` argument is given to tell [Xarray](https://foundations.projectpythia.org/core/xarray) how to load the metadata for this source. Zarr data may contain consolidated metadata. If it does, using it can increase performance significantly.\n",
     "\n",
     "When you use Intake's `open_{driver}` methods, it creates a catalog entry for the source. You can view the yaml using the source's `yaml` method."
    ]

notebooks/intake_introduction.ipynb

@@ -41,9 +41,9 @@
     "\n",
     "| Concepts | Importance | Notes |\n",
     "| --- | --- | --- |\n",
-    "| [Times and Dates in Python](https://foundations.projectpythia.org/core/datetime/datetime.html) | Necessary | |\n",
-    "| [Intro to Xarray](https://foundations.projectpythia.org/core/xarray/xarray-intro.html) | Necessary | |\n",
-    "| [Intro to Cartopy](https://foundations.projectpythia.org/core/cartopy/cartopy.html) | Helpful | |\n",
+    "| [Times and Dates in Python](https://foundations.projectpythia.org/core/datetime/datetime) | Necessary | |\n",
+    "| [Intro to Xarray](https://foundations.projectpythia.org/core/xarray/xarray-intro) | Necessary | |\n",
+    "| [Intro to Cartopy](https://foundations.projectpythia.org/core/cartopy/cartopy) | Helpful | |\n",
     "| [Understanding of Zarr](https://zarr.readthedocs.io/en/stable/) | Helpful | |\n",
     "| [Understanding of Dask](https://www.dask.org/) | Helpful | |\n",
     "\n",
@@ -168,7 +168,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "From this Python dictionary, there are a few things that we can learn. The `container` key tells us what form the data will be in when we read it. In this case it will be a [Xarray](https://foundations.projectpythia.org/core/xarray.html) `Dataset` The `user_parameters` key has a list containing parameters a user can set to control what data they get. The `metadata` key contains an arbitrary dictionary of information specified by the catalog author. A common things to find in the `metadata` field are plots you can use to get a quick peak at the data."
+    "From this Python dictionary, there are a few things that we can learn. The `container` key tells us what form the data will be in when we read it. In this case it will be a [Xarray](https://foundations.projectpythia.org/core/xarray) `Dataset` The `user_parameters` key has a list containing parameters a user can set to control what data they get. The `metadata` key contains an arbitrary dictionary of information specified by the catalog author. A common things to find in the `metadata` field are plots you can use to get a quick peak at the data."
    ]
   },
   {
@@ -284,7 +284,7 @@
    "source": [
     "Mesowest provides a [tutorial](https://mesowest.utah.edu/html/hrrr/zarr_documentation/html/xarray_one_day_analysis_example.html) for reading a days worth of surface temperature HRRR data from AWS. Lets see what the same task looks like using Intake.\n",
     "\n",
-    "We will start by setting up our [Cartopy](https://foundations.projectpythia.org/core/cartopy.html) projection according to the information given in the readme source."
+    "We will start by setting up our [Cartopy](https://foundations.projectpythia.org/core/cartopy) projection according to the information given in the readme source."
    ]
   },
   {
@@ -304,7 +304,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now lets read in the data with Intake. To do this will create a [datetime](https://foundations.projectpythia.org/core/datetime.html) object with the date August 9, 2019. Then we will use list comprehension and `timedelta` objects to create a [datetime](https://foundations.projectpythia.org/core/datetime.html) object for each hour that day. Again, using list comprehension, we will create a list of datasets using Intake. In order to concatenate our list of datasets using [Xarray](https://foundations.projectpythia.org/core/xarray.html), we need a dimension to concatenate accross. Each dataset in our list contains a time variable with an array of just one timestamp. We can promote that variable to a coordinate using the `set_coords` method. This may take a few minutes to run."
+    "Now lets read in the data with Intake. To do this will create a [datetime](https://foundations.projectpythia.org/core/datetime) object with the date August 9, 2019. Then we will use list comprehension and `timedelta` objects to create a [datetime](https://foundations.projectpythia.org/core/datetime) object for each hour that day. Again, using list comprehension, we will create a list of datasets using Intake. In order to concatenate our list of datasets using [Xarray](https://foundations.projectpythia.org/core/xarray), we need a dimension to concatenate accross. Each dataset in our list contains a time variable with an array of just one timestamp. We can promote that variable to a coordinate using the `set_coords` method. This may take a few minutes to run."
    ]
   },
   {
@@ -325,7 +325,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now our data is ready to be analyzed in the normal way using [Xarray](https://foundations.projectpythia.org/core/xarray.html)."
+    "Now our data is ready to be analyzed in the normal way using [Xarray](https://foundations.projectpythia.org/core/xarray)."
    ]
   },
   {
@@ -371,7 +371,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "As you can see [Xarray](https://foundations.projectpythia.org/core/xarray.html) uses Dask arrays instead of [NumPy](https://foundations.projectpythia.org/core/numpy.html) arrays to hold the data when the `to_dask` method is used."
+    "As you can see [Xarray](https://foundations.projectpythia.org/core/xarray) uses Dask arrays instead of [NumPy](https://foundations.projectpythia.org/core/numpy) arrays to hold the data when the `to_dask` method is used."
    ]
   },
   {
@@ -391,7 +391,7 @@
     "- Intake can load data into Dask for use in parallel computing. \n",
     "\n",
     "### What's next?\n",
-    "In the next notebook we will look at writing a Intake catalog and making it available on [Github](https://foundations.projectpythia.org/foundations/getting-started-github.html)."
+    "In the next notebook we will look at writing a Intake catalog and making it available on [Github](https://foundations.projectpythia.org/foundations/getting-started-github)."
    ]
   },
   {