Cleanup and fixing some typos

RTIInternational · Jul 8, 2024 · 3e33f2a · 3e33f2a
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diff --git a/docs/sphinx/getting_started/data_model.rst b/docs/sphinx/getting_started/data_model.rst
@@ -8,7 +8,7 @@ This is intended to be a living document that provides a common data model to wo
 
 Timeseries
 ----------
-The ``timeseries`` data model (mostly taken from [HydroTools](https://github.com/NOAA-OWP/hydrotools)) describes the schema used to store, you guessed it, timeseries data from both observed and simulated sources.  In the context of this system, this data model will be utilized as the format to store data as parquet files.  As such, a standard file directory structure is also important.  See [Cache Directory Structure] below.
+The ``timeseries`` data model (mostly taken from `HydroTools <https://github.com/NOAA-OWP/hydrotools>`_) describes the schema used to store, you guessed it, timeseries data from both observed and simulated sources.  In the context of this system, this data model will be utilized as the format to store data as parquet files.  As such, a standard file directory structure is also important.
 
 - ``reference_time``: [datetime] This is a reference time for a particular model simulation.
 - ``value_time``: [datetime] This is the time a value is valid at.

diff --git a/docs/sphinx/getting_started/index.rst b/docs/sphinx/getting_started/index.rst
@@ -86,7 +86,7 @@ To fetch and load retrospective NWM point data (ie, streamflow), you can import
 Model Evaluation
 ^^^^^^^^^^^^^^^^
 
-TEEHR provides a set of classes for evaluating model performance using ``DuckDB`` either with parquet files
+TEEHR provides a set of classes for evaluating model performance using `DuckDB <https://duckdb.org/>`_ either with parquet files
 or a persistent database. To evaluate a model based on a parquet file of pre-joined timeseries data, you can
 import the ``DuckDBJoinedParquet`` class:
 

diff --git a/docs/sphinx/getting_started/queries.rst b/docs/sphinx/getting_started/queries.rst
@@ -3,7 +3,7 @@
 Model Evaluation Queries
 ========================
 
-The TEEHR data library provides tools for querying data from the cached parquet files and for generating metrics.  This includes:
+The TEEHR data library provides tools for querying data from the cached parquet files or database and for generating metrics.  This includes:
 
 * Get Timeseries
 * Get Timeseries Characteristics
@@ -22,7 +22,7 @@ This feature returns simple summary statistics on the requested timeseries.
 
 Get Joined Timeseries
 ---------------------
-This feature joined two different tables of timeseries together based on location and time, applies filters and returns the paired timeseries
+This feature joins two different tables of timeseries together based on location and time, applies filters and returns the paired timeseries
 
 .. figure:: ../../images/getting_started/joined_timeseries.png
    :scale: 75%

diff --git a/docs/sphinx/index.rst b/docs/sphinx/index.rst
@@ -20,8 +20,8 @@ TEEHR (pronounced "tier") is a python tool set for loading, storing, processing
         :class-card: intro-card
         :shadow: md
 
-        New to *TEEHR*? Check out the getting started guides. They contain an
-        introduction to *TEEHR'* main concepts and links to additional tutorials.
+        New to TEEHR? Check out the getting started guides. They contain an
+        introduction to TEEHR main concepts and links to additional tutorials.
 
         +++
 
@@ -39,7 +39,7 @@ TEEHR (pronounced "tier") is a python tool set for loading, storing, processing
         :shadow: md
 
         The user guide provides in-depth information on the
-        key concepts of pandas with useful background information and explanation.
+        key concepts of TEEHR with useful background information and explanation.
 
         +++
 

diff --git a/docs/sphinx/tutorials/grouping_and_filtering.rst b/docs/sphinx/tutorials/grouping_and_filtering.rst
@@ -10,7 +10,7 @@ we could group the ``configuration`` field to calculate performance metrics for
 
 We could then include filters to further narrow the population subset such as only considering first order stream locations or
 locations below a certain mean slope value. This allows us to gain more insight into the model performance through specific
-quantitave and analysis.
+quantitative analysis.
 
 .. note::
     The grouping and filtering capabilities in TEEHR provide the ability to explore models across

diff --git a/docs/sphinx/tutorials/joining_timeseries.rst b/docs/sphinx/tutorials/joining_timeseries.rst
@@ -6,7 +6,7 @@ Joining Timeseries
 One of the first and most important steps in comparing simulated and observed timeseries data is to join
 the two datasets together based on location and time (and potentially other fields).
 
-In this example, we consider a comparison of National Water Model (NWM) v3.0 retropective
+In this example, we consider a comparison of National Water Model (NWM) v3.0 retrospective
 streamflow simulations ("secondary") to USGS observed streamflow data ("primary") for a few
 time steps at five different locations (gage stations).
 

diff --git a/docs/sphinx/user_guide/notebooks/loading_examples_index.rst b/docs/sphinx/user_guide/notebooks/loading_examples_index.rst
@@ -7,7 +7,7 @@ Fetching and Loading Examples
    :maxdepth: 2
 
    NWM Operational Point Data </user_guide/notebooks/loading/point_loading_example>
-   NWM Operational Gridded Data [WIP] </user_guide/notebooks/loading/grid_loading_example>
-   NWM Retrospective Point Data [WIP] </user_guide/notebooks/loading/load_retrospective>
-   NWM Retrospective Gridded Data [WIP] </user_guide/notebooks/loading/load_retrospective>
-   USGS Streamflow Data [WIP] </user_guide/notebooks/loading/load_retrospective>
+   NWM Operational Gridded Data </user_guide/notebooks/loading/grid_loading_example>
+   NWM Retrospective Point Data </user_guide/notebooks/loading/load_retrospective>
+   NWM Retrospective Gridded Data </user_guide/notebooks/loading/load_gridded_retrospective>
+   USGS Streamflow Data </user_guide/notebooks/loading/usgs_loading>