Merge pull request #211 from DunklesArchipel/features

Changed Advantages to Features in the documentation

README.md

@@ -5,12 +5,12 @@
 The `svgdigitizer` allows recovering data from a curve in a figure, plotted in a 2D coordinate system, which is usually found in scientific publications.
 The data is accessible either with a command line interface or the API from a specifically prepared scaled vector graphics (SVG) file. The data can be stored as a [frictionless datapackage](https://frictionlessdata.io/) (CSV and JSON) which can be used with [unitpackage](https://echemdb.github.io/unitpackage/) to access the plots metadata or create a database of such datapackages.
 
-# Advantages
+# Features
 
-The `svgdigitizer` has some advantages compared to other plot digitizers, such as:
+The `svgdigitizer` has additional features compared to other plot digitizers, such as:
 
 * supports **multiple y (x) values per x (y) value**
-* usage of splines allows for very **precise retracing** distinct features
+* usage of splines allows for very **precise retracing** of distinct features
 * splines can be digitized with specific **sampling intervals**
 * supports plots with distorted/**skewed axis**
 * **extracts units** from axis labels
@@ -32,7 +32,7 @@ This package is available on [PiPY](https://pypi.org/project/svgdigitizer/) and
 pip install svgdigitizer
 ```
 
-The package is also available on [conda-forge](https://github.com/conda-forge/svgdigitizer-feedstock) an can be installed with conda
+The package is also available on [conda-forge](https://github.com/conda-forge/svgdigitizer-feedstock) and can be installed with conda
 
 ```sh .noeval
 conda install -c conda-forge svgdigitizer
@@ -102,4 +102,4 @@ commonly found in the field of electrochemistry.
 >>> cv = CV(SVGPlot(SVG(open(cv_svg, 'rb')), sampling_interval=0.01))
 ```
 
-The resulting `cv` object has the same properties than the `figure` object above.
+The resulting `cv` object has the same properties as the `figure` object above.

doc/index.md

@@ -26,10 +26,28 @@ Welcome to svgdigitizer's documentation!
 ========================================
 
 The `svgdigitizer` allows recovering data from a curve in a figure,
-plotted in a 2D coordinate system. The data can be recovered from an SVG with a Python API or a command line interface to create figures or [frictionless datapackages](https://frictionlessdata.io/) (CSV and JSON). The `svgdigitizer` supports units, scalebars, scaling factors, and [more](#advantages).
+plotted in a 2D coordinate system. The data can be recovered from an SVG with a Python API or a command line interface to create figures or [frictionless datapackages](https://frictionlessdata.io/) (CSV and JSON). The `svgdigitizer` supports units, scalebars, scaling factors, and more.
 
 ![files/logo/logo.png](files/logo/logo.png)
 
+Features
+============
+
+The `svgdigitizer` has additional features compared to other plot digitizers:
+
+* usage of splines allows for very **precise retracing** of distinct features
+* supports **multiple y (x) values per x (y) value**
+* supports **scale bars**
+* supports **scaling factors**
+* supports plots with a **skewed axis**
+* splines can be digitized with specific **sampling intervals**
+* **extracts units** from axis labels
+* **extracts metadata** associated with the plot in the SVG
+* **reconstruct time series** with a given scan rate
+* **saves data as [frictionless datapackage](https://frictionlessdata.io/)** (CSV + JSON) allowing for [FAIR](https://en.wikipedia.org/wiki/FAIR_data) data usage
+* **inclusion of metadata** in the datapackage
+* **Python API** to interact with the retraced data
+
 ## Example Plot
 
 Such plots are often found in scientific publications, where
@@ -113,24 +131,6 @@ A plot can be created via
 figure.plot() # Or plot.plot() for an svgplot instance.
 ```
 
-Advantages
-============
-
-The `svgdigitizer has some advantages compared to other plot digitizers:
-
-* usage of splines allows for very **precise retracing** distinct features
-* supports **multiple y (x) values per x (y) value**
-* supports **scale bars**
-* supports **scaling factors**
-* supports plots with **skewed axis**
-* splines can be digitized with specific **sampling intervals**
-* **extracts units** from axis labels
-* **extracts metadata** associated with the plot in the SVG
-* **reconstruct time series** with a given scan rate
-* **saves data as [frictionless datapackage](https://frictionlessdata.io/)** (CSV + JSON) allowing for [FAIR](https://en.wikipedia.org/wiki/FAIR_data) data usage
-* **inclusion of metadata** in the datapackage
-* **Python API** to interact with the retraced data
-
 +++
 
 Installation