G: To count only non-blank visible cells in a range (excluding cells that appear blank due to formulas or filters), you can use an array formula combined with SUBTOTAL and LEN. Here's how:

1. Assume your range is A1:A100.

2. Use this formula:

   =SUMPRODUCT(SUBTOTAL(103,OFFSET(A1:A100,ROW(A1:A100)-MIN(ROW(A1:A100)),0,1)),LEN(A1:A100)>0)

Explanation:

• SUBTOTAL(103, ...): Counts only visible cells when filters are applied.
• LEN(A1:A100)>0: Checks if the cell is truly non-blank (ignores formulas returning empty strings).
• SUMPRODUCT: Combines the two conditions to count non-blank visible cells.

How to Enter:

1. Copy and paste the formula into the desired cell.
2. Press Enter (no need for Ctrl+Shift+Enter in newer LibreOffice versions).

This method should bypass your issue with filters and formulas.

G: Yes, the formula will work for text values. Here's why:

• LEN(A1:A100) > 0 checks if the length of the text (or value) in a cell is greater than 0. This condition ensures that even if the cell contains text, it will be counted as long as it is not empty (and visible).

It will exclude:

• Truly blank cells.
• Cells with formulas returning "" (empty strings).
• Hidden rows when a filter is applied.

So, it effectively counts only the visible, non-blank cells, including those containing text.

G: Here are some ideas for accessible and varied datasets you can use to practice Power Query:

Publicly Available Datasets:

1. Kaggle

   • Website: https://www.kaggle.com
   • Offers a vast collection of datasets, ranging from beginner to advanced, on topics like sales, healthcare, and sports.

2. Google Dataset Search

   • Website: https://datasetsearch.research.google.com
   • Allows you to search for datasets from various sources on almost any topic.

3. Data.gov

   • Website: https://data.gov
   • Official U.S. government portal for open data, with datasets on demographics, environment, finance, and more.

4. World Bank Open Data

   • Website: https://data.worldbank.org
   • Provides datasets on global development indicators like GDP, population, and education.

5. OpenStreetMap (OSM)

   • Website: https://www.openstreetmap.org
   • Offers location and geospatial datasets for practice with mapping and geographical data.

Simple, Everyday Data Sources:

6. CSV Exports from Tools You Use

   • Export data from tools like Google Analytics, Spotify playlists, or workout trackers to clean and transform.

7. Online Retailers

   • Many e-commerce sites allow you to download order histories or product lists as CSVs. Great for practicing joins, filtering, and aggregations.

8. Wikipedia Tables

   • Find structured tables on Wikipedia (like country populations or sports stats). You can import these directly using Power Query's web connector.

9. Movie Databases

   • Websites like IMDb or TMDb have APIs or CSVs for movie data. Example: Analyze box office trends or actor appearances.

10. Supermarket Price Lists

    • Download or scrape grocery store product prices from online catalogs to practice pricing analysis or inventory management.

For Fun:

11. Fantasy Sports Data

    • Use player stats, game results, or draft histories for data cleaning and transformation exercises.

12. Board Game Data

    • BoardGameGeek (https://boardgamegeek.com) has a rich dataset for analysis of game ratings, playtimes, and categories.

13. Music Charts

    • Use Billboard charts or Spotify playlist data to analyze trends in music popularity.

Miscellaneous:

14. Stock Market Data

    • Download stock prices from Yahoo Finance or other financial sites. Great for time-series transformations.

15. Weather Data

    • Websites like NOAA or WeatherAPI offer downloadable data for temperature, rainfall, and other variables.

16. Survey Data

    • Use anonymized survey results from platforms like Kaggle or your own exported survey responses from tools like Google Forms.

Let me know if you'd like specific instructions for connecting any of these to Power Query!