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Optimal Wordle Strategy Data
Data Science and Analytics
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About
Details optimal strategic word sequences required to solve the daily five-letter Wordle puzzle. The primary purpose is to outline decision paths that minimise the number of guesses needed to identify the target word. Analysis demonstrates strong performance, showing an average of 3.4201 guesses when playing in Normal mode and 3.5076 guesses required in Hard mode.
Columns
The data is structured into 10 distinct columns, detailing the sequence of up to five guesses and the resulting feedback, referred to as 'hits'.
- word_0: The initial word recommended in the sequence. For all records, this word is 'salet'.
- hits_0: The feedback received after the first word is guessed (e.g., 'BBBBB').
- word_1: The second word suggested to be guessed.
- hits_1: The feedback received after the second word is guessed.
- word_2: The third word suggested.
- hits_2: The feedback received after the third word is guessed.
- word_3: The fourth word suggested.
- hits_3: The feedback received after the fourth word is guessed.
- word_4: The fifth word suggested.
- hits_4: The feedback received after the fifth word is guessed.
Distribution
The dataset is provided in a CSV DataFrame format. It includes 10 columns and contains 2,309 records or rows. The file size is approximately 138.61 kB. The data is static, as the expected update frequency is never.
Usage
This strategic sequence data is ideal for various applications, including:
- Developing sophisticated Wordle solver applications or bots.
- Studying optimal decision-tree analysis in the context of information entropy and puzzles.
- Building AI agents focused on efficient strategy implementation.
- Analysing techniques in text and literature based on word structure and efficient pattern matching.
Coverage
This dataset represents derived strategic pathways designed for winning the game under specified parameters. It focuses exclusively on providing sequences for both Normal and Hard playing modes of the Wordle game. It is not bound by traditional geographic, time range, or demographic limits.
License
CC0: Public Domain
Who Can Use It
- Data Scientists: For advanced experimentation with search algorithms, information theory, and text-based problem solving.
- Academics/Researchers: To study efficient problem-solving strategies and word choice optimisation.
- Software Engineers: To integrate high-performing solver logic into software applications or platforms.
- Puzzles Enthusiasts: To understand and implement proven strategies to improve personal gameplay.
Dataset Name Suggestions
- Wordle Strategies (3.42 avg guesses)
- Alex Selby's Optimal Wordle Sequence Data
- Minimal Guess Wordle Paths
- Wordle Solver Logic Data
Attributes
Original Data Source:Optimal Wordle Strategy Data
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