links fixed

DOCS/_first_steps.md

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 Installing Python for data science
 -------------
 
-GrainSizeTools script requires [Python](https://www.python.org/ ) 3.6 or higher and the Python scientific libraries [*NumPy*](http://www.numpy.org/ ) [*SciPy*](http://www.scipy.org/ ), [*Pandas*](http://pandas.pydata.org ) and [*Matplotlib*](http://matplotlib.org/ ). If you have no previous experience with Python, I recommend downloading and installing the [Anaconda Python distribution](https://www.anaconda.com/distribution/ ) (Python 3.x version), as it includes all the required the scientific packages (> 5 GB disk space). In case you have a limited space in your hard disk, there is a distribution named [miniconda](http://conda.pydata.org/miniconda.html ) that only installs the Python packages you actually need. For both cases you have versions for Windows, MacOS and Linux.
+GrainSizeTools script requires [Python](https://www.python.org/ ) 3.6 or higher and the Python scientific libraries [*NumPy*](http://www.numpy.org/ ) [*SciPy*](http://www.scipy.org/ ), [*Pandas*](http://pandas.pydata.org ) and [*Matplotlib*](http://matplotlib.org/ ). If you have no previous experience with Python, I recommend downloading and installing the [Anaconda Python distribution](https://docs.anaconda.com/free/anaconda/install/), as it includes all the required the scientific packages (> 5 GB disk space). In case you have a limited space in your hard disk, there is a distribution named [Miniconda](https://docs.conda.io/projects/miniconda/en/latest/) that only installs the Python packages you actually need. For both cases you have versions for Windows, MacOS and Linux.
 
-Anaconda Python Distribution: https://www.anaconda.com/distribution/ 
+Anaconda Python Distribution: https://docs.anaconda.com/free/anaconda/install/
 
-Miniconda: http://conda.pydata.org/miniconda.html 
-
-Once Anaconda is installed, launch the Anaconda Navigator and you will see that you have installed three different scientific-oriented integrated development systems (IDEs): **Spyder**, **JupyterLab**, and **Jupyter Notebook**. The GrainSizeTools documentation is written assuming that you will carry out the work in one of these IDEs (see next section). 
-
-> 👉 Scope: The GrainSizeTools script is not designed to deal with microscopic images but to analyse and visualize grain size populations and estimate stresses via paleopiezometers. **It is therefore necessary to measure the grain diameters or the sectional areas/volumes of the grains in advance and store them in a txt/csv/excel file**. For this task, we highly encourage you to use the [*ImageJ*](http://rsbweb.nih.gov/ij/) application or one of their different flavours (see [here](http://fiji.sc/ImageJ)). ImageJ-type applications are public-domain image processing programs widely used for scientific research that runs on Windows, macOS, and Linux platforms. The documentation contains a quick tutorial on how to measure the areas of the grain profiles with ImageJ, see *Table of Contents*. The combined use of **ImageJ** and **GrainSizeTools script** is intended to ensure that all data processing steps are done through free and open-source programs/scripts that run under any operating system. If you are dealing with EBSD data instead, we encourage you to use the [MTEX toolbox](https://mtex-toolbox.github.io/) for grain reconstruction (a tutorial on this will be available soon).
+Miniconda: https://docs.conda.io/projects/miniconda/en/latest/
 
+Once Anaconda is installed, launch the Anaconda Navigator and you will see that you have installed three different scientific-oriented integrated development systems (IDEs): **Spyder**, **JupyterLab**, and **Jupyter Notebook**. The GrainSizeTools documentation is written assuming that you will carry out the work in one of these IDEs (see next section).
 
+> [!IMPORTANT]
+> Scope: The GrainSizeTools script is not designed to deal with microscopic images but to analyse and visualize grain size populations and estimate stresses via paleopiezometers. **It is therefore necessary to measure the grain diameters or the sectional areas/volumes of the grains in advance and store them in a txt/csv/excel file**. For this task, we highly encourage you to use the [*ImageJ*](http://rsbweb.nih.gov/ij/) application or one of their different flavours (see [here](http://fiji.sc/ImageJ)). ImageJ-type applications are public-domain image processing programs widely used for scientific research that runs on Windows, macOS, and Linux platforms. The documentation contains a quick tutorial on how to measure the areas of the grain profiles with ImageJ, see *Table of Contents*. The combined use of **ImageJ** and **GrainSizeTools script** is intended to ensure that all data processing steps are done through free and open-source programs/scripts that run under any operating system. If you are dealing with EBSD data instead, we encourage you to use the [MTEX toolbox](https://mtex-toolbox.github.io/) for grain reconstruction (a tutorial on this will be available soon).
 
 ## Open and running the script