Python — Data Science December
A Python Data Science Digital Advent Calendar
Welcome to Python Data Science December. One story about Data Science with Python each day — from December 1st until December 24th. How does this sound to you? You can call it a digital data science advent calendar. 🎄
Together, we will work on awesome real-life projects. Some of them will be full-blown data science projects covering the whole range of Data Science that you can copy & add to your portfolio. Others will only cover one specific area of data science like crawling, transforming, or visualizing the data.
This story will be continuously updated each day from now to December 24th. Additionally, this story will be used to track some interesting KPIs like views, claps, earnings & more. See below the list of stories each day.
Overall, I have spent >150 hours implementing & writing these stories, so any support would be highly appreciated. In return, you will gain knowledge in Data Science & Python in the below areas and with the following libraries.
- 🔍 Data Analytics: Numpy, Pandas, CSV, JSON
- 📊 Plotting & Visualizations: Matplotlib, Plotly, Folium, Leaflet
- 📰 Web Scraping: Selenium, BeautifulSoup
- 📲 API-Calls: Requests, yfinance, Tweepy, Mapquest
- ⏩ Data Pipelines: Kafka, Pykafka
- 💻Web Development: Flask
You can support me in the following ways.
- 👏 Reading, clapping & commenting on my Stories
- 🔊 Tell your friends about the Python Data Science December
- 🔗 Signing up at Medium using my Link
- 🙏 Support me on Patreon and get advanced content
Now finally, let’s come to the list of Stories.
1️⃣ December 1 — Netflix Data Exploration
Today, we will explore our Netflix viewing activity using Python Pandas & Matplotlib. Together, we are getting the data, transforming the data, and visualizing the data. Have Fun!
2️⃣ December 2 — Web Scraping Restaurants
Today, it’s web scraping day. Together, we will crawl data from Starbucks, Subway & Mcdonald's restaurants in Berlin from the web. Happy Crawling!
3️⃣ December 3 — Address to Geolocation
Today we have a given dataset with addresses of different restaurants in Berlin. We will enrich this dataset with geolocation information — so the latitude & longitude values for the given addresses — by calling an API.
4️⃣ December 4 — Visualize data on a Map
We will use Python Folium to visualize a given list of restaurant addresses in Berlin as markers on a map. Happy coding!
5️⃣December 5— Live Stock Market Visualization
In today’s story, we will use the yfinance API for Python to get live stock market data that we will visualize on an interactive chart using Python Plotly.
6️⃣ December 6 — Premier League Twitter Activity
In today’s story, we will create our own dataset from scratch based on real & live Tweets from out there in the world. We will make use of Python Tweepy & Pandas.
7️⃣ December 7 — Twitter Visualization & Analytics
Today is visualization day. We will visualize the Twitter activity of the top six Premier League football clubs. Happy plotting.
8️⃣December 8— Python Sankey Diagrams
Sankey Diagrams are a great tool to visualize data flows. Today we will build our own Sankey Diagrams using Python Plotly
9️⃣December 9 — Crawl Nintendo Game Reviews
What is the best Nintendo Game ever? Today. we will crawl Nintendo game review data from Mobygames.com using Python BeautifulSoup. Happy crawling!
1️⃣0️⃣ December 10 — The Best Nintendo Games Ever
After crawling all Nintendo Game Reviews in the last story, we will explore & visualize the review ratings in this story.
1️⃣1️⃣ December 11 — Flight Data Generation
Today we start a new data science project about generating airplane location data. In the end, we will build something similar to what you might know from Flightradar24, but much smaller. We will not only learn about Python, Kafka & Pykafka but also about important data architectural concepts like separation of concerns & decoupling. But more about this later.
1️⃣2️⃣ December 12 — Flight Data Live Visualization
Today we will consume airplane location data and generate a live map with current flights and their position.
1️⃣3️⃣December 13 — Medium stats & earnings
Yesterday’s story marked the halftime of our Python Data Science December. Today it’s time to wrap things up & analyze what happened so far. We will make use of Python Pandas & Matplotlib to analyze the Mediums stats like views & earnings.
1️⃣4️⃣December 14 — Web Scraping Soccer World Cups
Today, we will make use of Python BeautifulSoup & Pandas to crawl the Wikipedia World Cup pages.
1️⃣5️⃣December 15 — Visualizing Soccer World Cup Data
We have a given dataset that we crawled from the Wikipedia World Cup pages before. We will use Pandas & Matplotlib to explore & visualize the data.
1️⃣6️⃣December 16 — S&P500 Bear Market Analysis
The global stock markets are currently under pressure and most of them entered a bear market. Today we will analyze the S&P 500 index performance compared to previous bear markets using Python Pandas & Matplotlib.
1️⃣7️⃣December 17 —COVID-19 Analysis
Each individual COVID-19 case is dramatic and each death is a tragedy, but is it still a threat to the major parts of our society? We will explore the COVID-19 cases & deaths over time for different countries in Europe using Python Pandas, Plotly & Matplotlib.
1️⃣8️⃣December 18 —Supply Chain Control Tower
What a coincidence. Writing about Covid yesterday, and being sick today. So I can not provide any own stories for December 18th and 19th. To not stop your learning or reading journey in Python Data Science, I will interlink amazing stories from other authors.
Today, Supply Chain Control Tower from Samir Saci. It’s an amazing read.
1️⃣9️⃣December 19 — Pie chart-like Visualizations, but cooler
As I am still being sick, another Python Data Science article from another great author today — Boriharn K. He is showing us 9 great visualizations that are way cooler compared to simple pie charts.
2️⃣0️⃣December 20 — Can AI be a data scientist?
As I am still being sick, another Python Data Science article from another great author today — Salvatore Raieli. He wrote a great article exploring if an AI can act as a data scientist. Have fun reading this great article.
2️⃣1️⃣December 21 — Interactive Weather Visualization
I have recovered but decided to keep on recommending Python Data Science stories from other authors. It simply covers a broader range of topics for you. Today, I recommend reading the article from Will Norris about interactive weather visualization with Python Plotly.
2️⃣2️⃣December 22— Bokeh Data Visualizations
Today, I am recommending reading the article from Payal Patel about creating data visualizations in Python with Bokeh. The story is really amazing.
2️⃣3️⃣December 23 —Anomaly Detection
Today, I will interlink the article from Peter Mqoaie about Anomaly Detection with Python. It is a great read.
2️⃣4️⃣December 24 —Medium Earnings & Stats
Wow, we made it. The last story of the Python Data Science December is there. This was an awesome journey and I am thankful for everyone who followed & supported me. I hope you learned as much as I did 🙏.
In the last story, we will take a look at the Medium statistics & earnings generated throughout this series.
