REAL PYTHON MINI PROJECTS.
DATA GATHERING, DATA STRUCTURES AND OOP PRACTICE
Maria Lymperaiou is a software engineer at JP Morgan Chase Bank in the UK. She has been researcher at the European Organization for Nuclear Research (CERN) in Switzerland and holds a ME Electrical and Computer Engineering.
DAVID ABRAM is a Data Scientist at MICROSOFT. He has been the CTO of an energy efficiency startup and he has also worked as research engineer at a big multinational of energy storage.
Based in the US, David holds a Ph.D. in Chemical Engineering (Stanford University).
This job consists of 3 projects and 1 assignment to practice several python topics while gathering data for different purposes. Moreover, you will be introduced to popular and extremely useful Python libraries like Pandas, Beautiful soup, Selenium, etc.
Don´t worry if you are not familiar with those libraries, the tasks involving the libraries are very basic. One of the goals of the following challenges is to get used to reading documentation and get the basics of new libraries to perform tasks more efficiently.
The projects are as follows:
1) Write a program to replicate the stock summary coming up when you enter a ticker on common search engines like Google or bing. It includes a basic web scraping exercise to extract stock symbols from the wikipedia and a data wrangling part to retrieve companies information from Yahoo Finance and store it in a Pandas data frame.
2) Write a program to take screenshots of search engines results and store the pictures in a new folder that will have to be created automatically. This project is the most challenging, it is based on the job many SEO analysts must perform to keep track of google keywords rankings but is an excellent exercise to practice functional programming and tasks automation. You will need to find out about the Selenium library.
3) Dictionary Fun: a data structure assignment. Given a nested dictionary, write a script to manipulate data and yield several lists in function of a given set of conditions.
4) Decision making program: create a program using object oriented programming that helps a user decide what activity is best for every day based on the likelihood of weather events such as rain, snow, fog, temperature and so on. There are many possible combinations so you will have to write methods including conditional statements. Inputs (weather events) are in an Excel file, so you will need pandas library to import the data.
DOWNLOAD / CONTENT
You will receive an email with a protected ZIP and a password to access the content. If you are a registered user, the download is always available on your account.
The downloadable zip is made up of:
1) INSTRUCTIONS. A PDF with the project descriptions. It includes a guidelines section to help you complete the challenge step by step. The project is broken down in several exercises or hints that may follow in case you get lost.
2) SOLUTIONS. For project one and four, solutions come in a Jupiter Notebook. For project two and three, you will receive a py file.
All of them include comments and explanations about how the code works.
IMPORTANT: to see the solutions (Notebook) you need to have Jupyter or the ANACONDA package installed on your machine. If you do not have it, you may download it here. It is free.
WHAT YOU WILL PRACTICE
– Basic Web Scraping with Beautiful soup.
– Import/read Excel files with Pandas library.
– Matplotlib library to create charts.
– Loops. In all projects you will have to implement for loops.
– Conditional statements.
– Dates. In project two, you will have to work with dates and the datatime library.
– Create and name folders and files on the desktop with the OS library.
– Write functions.
– List comprehensions.
These exercises are for students that have finished a python bootcamp/ online course or data science master and need to practice solving real life problems.
If you need additional information, do not hesitate to contact us.
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