Cleaning data and clusterization methods

Cleaning/README.md

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+# Machine Learning Specialization
+---
+## Requirements
+### Python Scripts
+
+ *   Allowed editors: vi, vim, emacs
+ *   All your files will be interpreted/compiled on Ubuntu 16.04 LTS using python3 (version 3.5)
+ *   Your files will be executed with numpy (version 1.15)
+ *   All your files should end with a new line
+ *   The first line of all your files should be exactly #!/usr/bin/env python3
+ *   A README.md file, at the root of the folder of the project, is mandatory
+ *   Your code should follow pycodestyle (version 2.5)
+ *   All your modules should have documentation (python3 -c 'print(__import__("my_module").__doc__)')
+ *   All your classes should have documentation (python3 -c 'print(__import__("my_module").MyClass.__doc__)')
+ *   All your functions (inside and outside a class) should have documentation (python3 -c 'print(__import__("my_module").my_function.__doc__)' and python3 -c 'print(__import__("my_module").MyClass.my_function.__doc__)')
+ *   Unless otherwise noted, you are not allowed to import any module
+ *   All your files must be executable
+ *   The length of your files will be tested using wc
+
+---
+## More Info
+Installing Ubuntu 16.04 and Python 3.5
+
+Follow the instructions listed in Using Vagrant on your personal computer, with the caveat that you should be using ubuntu/xenial64 instead of ubuntu/trusty64.
+
+Python 3.5 comes pre-installed on Ubuntu 16.04. How convenient! You can confirm this with python3 -V
+Installing pip 19.1
+
+```
+wget https://bootstrap.pypa.io/get-pip.py
+sudo python3 get-pip.py
+rm get-pip.py
+```
+To check that pip has been successfully downloaded, use pip -V. Your output should look like:
+```
+$ pip -V
+pip 19.1.1 from /usr/local/lib/python3.5/dist-packages/pip (python 3.5)
+```
+Installing numpy 1.15, scipy 1.3, and pycodestyle 2.5
+```
+$ pip install --user numpy==1.15
+$ pip install --user scipy==1.3
+$ pip install --user pycodestyle==2.5
+```
+To check that all have been successfully downloaded, use pip list.
+Tasks
+
+---
+## Authors
+
+* **Robinson Montes** - [mecomonteshbtn](https://github.com/mecomonteshbtn)
+