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The Fundamentals of Data-driven Storytelling
The Fundamentals of Data-driven Storytelling
  • About this course
    • Course Introduction
  • Module 1 - Find
    • 1.1 How to Find Data for Storytelling and journalism
      • Starting with a question
      • Open data portals and platforms
      • Other sources of data
    • 1.2 How to get better data from a Goolge Search
      • Searching for filetypes and formats
      • More on Advanced Search operators
      • Other common Google Search operators
    • 1.3 Sourcing your own data
      • Creating a Google Form for Research
      • Creating a questionnaire with TypeForm
      • Using quizzes and comments as a sources of data
  • Module 2 - Get
    • 2.1 Turning websites and PDFs into machine readable data
      • Scraping data with Tabula
    • 2.2 An introduction to spreadsheet software
      • Google Sheets, Microsoft Excel and Libre Office Calc.
      • Finding your way around a spreadsheet
      • Simple web scraping with Google Sheets
  • Module 3 - Verify
    • 3.1 Can I use this data in my work?
      • Initial steps for verification
      • What do these column headings mean?
  • Module 4 - Clean
    • 4.1 What to do with disorganised data?
      • Why is clean data important?
      • Keep your data organised
      • Cleaning data cheatsheet
  • Module 5 - Analyse
    • 5.1 What is the story within the data?
      • Spreadsheet rows, columns, cells and tabs
        • Spreadsheet formats, forumlas and essential shortcuts
          • Using the VLOOKUP Function
            • Combine Data From Multiple Spreadsheets
    • 5.2 How to turn numbers into stories
  • Module 6 - Visualise
    • 6.1 Ways we visualise data
    • 6.2 Why we visualize Data
    • 6.3 How to visualise data
  • Course Testing & Feedback
    • ⏱️Quick course exam
    • 🎓Extended course exam
    • 📝Survey and feedback
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  1. Module 2 - Get
  2. 2.2 An introduction to spreadsheet software

Google Sheets, Microsoft Excel and Libre Office Calc.

The most common data formats that you will come across are CSV (.csv) and Microsoft Excel (.xlsx). These are not the only ways to store data, however.

  • .xls and .xlsx can be opened with Excel, Google Sheets or any other spreadsheet software. Excel files are a proprietary format though, and can only be read in spreadsheet applications.

  • .csv and .tsv are structured data formats:

    • “comma separated values” and “tab separated values”:

  • this means each value in the dataset is separated by either a comma or a tab, and that the data itself is stored in a plain text format. This means CSVs can be read in a text editor and are at less risk of file corruption or misreading.

  • Data can also be formatted for database software, such as the popular SQL format.

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Last updated 2 years ago