If this question in inappropriate for Data Science Stack Exchange, but there is another one within this stack it would be appropriate for, please let me know! It looks borderline to me.

A member of my research team (link to our GitHub Repo for this project, the xlx file referenced is called "Runway data") just scraped data on airport runways at airports within the United States which arial firefighting aircraft owned, operated, or contracted by the US Forest Service take off from on firefighting missions or land at afterwards. This is what it looks like after she scraped it,

enter image description here

My original plan was just to either transpose it, then use text-to-columns to create different fields/columns for each different feature or characteristic of each runway, but about 15 minutes into this, I discovered that a few of the records, less than 5% of them though I would say, have data on more than just the 5 characteristics data are included on in the first 3 records in the screenshot.

Is there anyway to get around this using Excel, MySQL, Dbeaver, Python, R or Tableau??

  • 1
    $\begingroup$ If I understand it correctly you want to extract the different features from the text, which can do in python using the pandas library to load the data and split the text on the newlines character (since each line is a separate feature) using str.split. $\endgroup$
    – Oxbowerce
    Feb 25 at 15:11


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