How I made first project in Python

I completed my first project in Python, today. It is tiny, tiny, tiny step for humans, of course, but significant step on my Data Science journey. Before I share it with you, let me tell you few word about beginning of my journey.

IBM Data Science Professional Certificate

In February 2021 started with "IBM Data Science Professional Certificate" on Coursera. Program consist of 10 courses:

  1. What is Data Science?
  2. Tools for Data Science
  3. Data Science Methodology
  4. Python for Data Science, AI & Development
  5. Python Project for Data Science
  6. Databases and SQL for Data Science with Python
  7. Data Analysis with Python
  8. Data Visualization with Python
  9. Machine Learning with Python
  10. Applied Data Science Capstone
As for now, it is relatively easy to learn if you focus, follow each step, test everything and play with tools outside of the course. Anyway, I may say that most important is curiosity. You are free to adapt your learning speed to your needs and possibilities. Even if you feel like giving up in some moment, trust me. First time you actually manage to make some useful code, everything will change.


My first project in Python


Task of the project was to  assume the role of a Data Scientist / Data Analyst working for a new startup investment firm that helps customers invest their money in stocks. I had to extract financial data like historical share price and quarterly revenue through web-scrapping or Yahoo Finance using Python in Jupyter Notebook. And than - the beautiful soup! I absolutely love the name for this library. "Beautiful Soup is a Python library for pulling data out of HTML and XML files. It works with your favorite parser to provide idiomatic ways of navigating, searching, and modifying the parse tree. It commonly saves programmers hours or days of work."

Here is the part of the code that you will be able to write in the middle of IBM Data Science Professional Certificate programme:

gme_revenue = pd.DataFrame(columns=["Date", "Revenue"])

tables = soup.find_all('table') 

for index,table in enumerate(tables):


    if ("GameStop Quarterly Revenue" in str(table)):

        table_index = index


        for row in tables[table_index].tbody.find_all("tr"):
            col = row.find_all("td")
            if (col != []):
                Date = col[0].text
                Revenue = col[1].text
                gme_revenue = gme_revenue.append({"Date":Date,"Revenue":Revenue}, ignore_index=True)

gme_revenue

Nice, isn't it? I may say only "Hello, Data Science!" in this moment. Now, I am going to learn about SQL and you are invited to comment, ask, discuss in case that you are interested in joining me on Data Science Journey!

Finally, here is small visualization of Tesla Stock that I created today.









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