Data analysis through python notebook
Classwork and homework assignments from Columbia Journalism School. Courses taught by Jonathan Soma.
Topics & tools include: Python, basic statistical analysis, OpenRefine, Carto, pandas, HTML, CSVs, APIs, csvkit, git/GitHub, cron, StackOverflow, data cleaning, command line tools, and more
- Cherry Blossoms Data
- Corperate Prosecution
- National Electronic Injury Surveillance System Data (NEISS)
- The Price of Weed
- Animal Dataset
- Billionaries
- Dark Sky API (Weather)
- Last FM API (Music)
- BeautifulSoup Scraping
- Mines Data
- NYTimes Front Page
- Teaxs Barber Violations
- Mines Data through Selenium
- Maryland Business Licenses
- Chicago Food Desert
- Using Geopandas
- Basic Mapping
- Spatial Joins
- Column Joins
- Using Basemap
- Power Plant Mapping
- Seaborns (Grapic Library)
- House sales and time data
- 311 Requests from NYPD
- Visa Percent Change and Reshaping
sentimental analysis, scikit-learn, text blob, etc.
- Classifier
- Cosine Similarity
- Couting and Stemming
- K-Means Clustering with scikit-learn
- Hip Pop Lyrics
- NRC Emotional Lexicon
- Trump vs State of the Union address analysis
- Wine Classifier
- Naive Bayes (Machine Learning) etc
- Reshape and Build Graphs
- Network Centrality
- NetworkX Graphs (Source-Target DataFrame)
- Marilyn Monroe Loves Visualization
- Network Calculation and Visualization