Update getting started_src.md

grammar improvements

DOCS/getting started_src.md

@@ -17,17 +17,17 @@ Once Python is installed, the next step is to download GrainSizeTools. Click on
 
 https://github.com/marcoalopez/GrainSizeTools/releases
 
-and download the latest version of the script by clicking in the the zip file as shown below
+and download the latest version of the script by clicking on the zip file as shown below
 
 TODO-> figure
 
-The GrainSizeTools folder contains the Python script code (several .py files) a folder named DATA, and various Jupyter notebooks (.ipynb files), which are templates for performing different types of grain size data analysis, either (i) quantifying grain size populations (apparent or real), (ii) performing stereological methods to approximate a true grain size distribution, or (iii) performing palaeopiezometry using the GrainSizeTools database. 
+The GrainSizeTools folder contains the Python script code (several .py files) a folder named DATA, and various Jupyter notebooks (.ipynb files), which are templates for performing different types of grain size data analysis, either (i) quantifying grain size populations (apparent or real), (ii) performing stereological methods to approximate a true grain size distribution, or (iii) performing palaopiezometry using the GrainSizeTools database. 
 
 TODO
 
 ## Run Jupyter notebooks and JupyterLab
 
-In order to improve the reproducibility of studies working with grain size populations, we suggest that the user works from the Jupyter notebooks templates provided by the script, especially if you have no previous experience with the Python language. To do this, it is necessary to open the notebooks either through the Jupyter notebooks application or through JupyterLab.
+To improve the reproducibility of studies working with grain size populations, we suggest that the user works from the Jupyter Notebooks templates provided by the script, especially if you have no previous experience with the Python language. To do this, it is necessary to open the notebooks either through the Jupyter Notebooks application or through JupyterLab.
 
 Briefly, [JupyterLab (or Jupyter Notebook)](https://jupyter.org/) (Fig. 2) provides an easy-to-use data science environment that allows you to create and share documents that may contain live code, equations, visualizations and narrative text. This is also ideal for generating reports and including them as supplementary material in your publications, so that any researcher can reproduce your data. JupyterLab is just the next generation of the “classic” Jupyter Notebook so you can use either one interchangeably (Fig. X).
 
@@ -41,15 +41,15 @@ TODO
 
 The script is organised in a modular way using different Python files and functions, both of which are intended to help modify, reuse and extend the code as necessary. In short, the script consists of seven Python files that must be in the same directory. These are the Python files and their main function:
 
-- ``GrainSizeTools.py``: This file takes care of importing all the submodules needed for the script to work. It is the Python file that is executed directly from the Jupyter Notebook templates.
-- ``averages.py``: This sub-module contains a set of functions for calculating different types of averages and margins of error.
-- ``plot.py``: This sub-module contains a set of functions for generating different types of ad hoc plots used by the script.
-- ``stereology.py``: This sub-module contains a set of functions to approximate true grain size distributions from sectional measurements using stereological methods.
-- ``piezometric_database.py``: This file contains the database of the various piezometers used by the script.
-- ``template.py``: This file contains the default options used by the Python Matplotlib library to generate plots.
+- ``GrainSizeTools.py``: This file imports all the modules needed for the script to work. This Python file is executed directly from the Jupyter Notebook templates.
+- ``averages.py``: This module contains a set of functions for calculating different types of averages and margins of error.
+- ``plot.py``: This module contains a set of functions for generating different types of ad hoc plots used by the script.
+- ``stereology.py``: This module contains a set of functions to approximate true grain size distributions from sectional measurements using stereological methods.
+- ``piezometric_database.py``: This file contains the database of piezometers the script uses.
+- ``template.py``: This file contains the default (Matplotlib) parameters used by the script to generate plots.
 - ``get.py``: This file contains the welcome message of the script.
 
-### Importing data using the Pandas library
+## Importing data using the Pandas library
 
 The way we propose to import the data to be analysed by the script is to use [Pandas](https://pandas.pydata.org/), which is the de facto standard Python library for data analysis and manipulation of tabular data (including CSV, Excel or text files). The library includes several tools for reading files and handling missing data. Once the GrainSizeTools script is run, all the Pandas methods are imported as ``pd`` and available once you write in a cell ``pd.``. TODO