Merge pull request #6 from Facundo-Barbera/1.1.1

Update 1.1.1

.gitignore

@@ -157,4 +157,4 @@ cython_debug/
 #  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
-#.idea/
+.idea/

README.md

@@ -1,51 +1,70 @@
-# U.S. Medical Insurance Costs
-This project, provided by Codecademy as part of the Data Science Foundations course, explores a dataset of medical insurance costs for individuals in the U.S. using statistical analysis techniques in Python 3.10 and Jupyter Notebook.
+# Exploratory Data Analysis of U.S. Medical Insurance Costs
+This project,
+provided by Codecademy as part of the Data Science Foundations course,
+explores a dataset of medical insurance costs for individuals in the U.S.
+using statistical analysis techniques in Python 3.11 and Jupyter Notebook.
 
-## Installation
+## Before You Begin
 
-Note:
 Before doing anything!
 Please note that there is a `reports` directory in this project.
 This directory contains the reports that I have generated using the Jupyter Notebook environment.
 These are HTML files that can be opened in any browser thus don't require Jupyter Notebook to be installed.
 Installing Jupyter can be troublesome, so I recommend opening the reports in the `reports` directory.
 
-If you want to run the project yourself, you will need to install any of following:
-- Python 3.10+ and Jupyter
+## Installation
+
+If you want to run the project yourself, you will need to install any of the following:
+- Python 3.11+
 - Conda environment(s)
 
-Additionally, you can install the `requirements.txt` which contains `matplotlib` package.
+Both of these installations require Jupyter to be installed,
+but Conda environments might have them installed by default
+depending on your environment configuration.
+
+You need to install the dependencies in the `requirements.txt` file if you want to run the notebook.
 
 You can install the `requirements.txt` file by running the following command in your terminal:
 ```bash
 pip install -r requirements.txt
 ```
-(Tip:
-You can write `pip install -r` and then drag
-and drop the `requirements.txt` file into the terminal to automatically write the path to the file)
+_(Tip: You can write `pip install -r` and then drag
+and drop the `requirements.txt` file into the terminal 
+to automatically write the path to the file)_
 
 ## Usage
 
-After installing Conda or Jupyter and other dependencies,
-you can run the project by running the following command in your terminal:
+I strongly recommend you first `cd` into the project directory before running the project,
+since it might be difficult to find the notebook otherwise.
+
+You can run the project (the Jupyter Notebook) by running the following command in your console:
 ```bash
 jupyter notebook
 ```
+This should open a browser window with the Jupyter Notebook environment on the directory you ran the command in.
+You will have to select the notebook on the page that opens.
 
-I strongly recommend you first `cd` into the project directory before running the command above,
-since it might be difficult to find the notebook otherwise.
 If you are using PyCharm, then you can execute the notebook directly in the editor.
-(Very cool, huh?)
-
-**_If you don't know what you are doing, refer to the note on installation._**
+_(I like to work like this, but I still recommend the browser version)_
 
 # Project Description
 
-For this project, you will be investigating a medical insurance costs dataset in a .csv file using the Python skills that you've developed. This dataset and its parameters will seem familiar if you've done any of the previous Python projects in the data science path.
-
-However, you're now tasked with working with the actual information in the dataset and performing your own independent analysis on real-world data! We will not be providing step-by-step instructions on what to do, but we will provide you with a framework to structure your exploration and analysis.For this project, you will be investigating a medical insurance costs dataset in a .csv file using the Python skills that you've developed. This dataset and its parameters will seem familiar if you've done any of the previous Python projects in the data science path.
-
-However, you're now tasked with working with the actual information in the dataset and performing your own independent analysis on real-world data! We will not be providing step-by-step instructions on what to do, but we will provide you with a framework to structure your exploration and analysis.
+For this project,
+you will be investigating a medical insurance costs dataset in a .csv file
+using the Python skills that you've developed.
+This dataset and its parameters will seem familiar
+if you've done any of the previous Python projects in the data science path.
+
+However,
+you're now tasked with working with the actual information in the dataset
+and performing your own independent analysis on real-world data!
+We will not be providing step-by-step instructions on what to do,
+but we will provide you with a framework to structure your exploration and analysis.
+For this project,
+you will be investigating a medical insurance costs dataset in a .csv file
+using the Python skills that you've developed.
+This dataset and its parameters will seem familiar
+if you've done any of the previous Python projects in the data science path.
 
 # Project Objectives
 
@@ -56,18 +75,11 @@ However, you're now tasked with working with the actual information in the datas
 - Optional: Document and organize your findings
 - Optional: Make predictions about a dataset’s features based on your findings
 
-## Personal Notes
-
-Firstly, I want to point out that this is my first Data Science project.
-I am really happy with the results.
-I have learned a lot about the Python programming language and the Jupyter Notebook environment.
-I also want to point out that this is not a data interpretation project.
-This is a project that focuses on the use of Python and Jupyter Notebook to analyze a dataset.
-
+## Project Evolution
 
-## Contributing
+This project is now considered complete.
+Although there is a lot of room for improvement,
+I have decided to move on to other projects.
+I might come back to this project in the future to implement some of the ideas I have for it.
 
-With the previous in mind, I am not looking for contributions to this project.
-I will accept suggestions and minor fixes, but I will not accept any major changes.
 
-This is a finished project.