Distinct value
A distinct value is a value different from others in a collection, counted once regardless of how many times it occurs.
Starting Data Analytics with Generative AI and Python
A unique value is a distinct value occurring in a field or variable, counted once regardless of its frequency.
- How it is used
- Checks how many different identifiers or categorical values occur before cleaning data or interpreting a business count.
- How deep it goes
- Demonstrates pandas counts and grouped identifier checks, but does not establish whether the identifiers denote different real-world customers.
- Examples
- Uses customer identifier columns and a grouped count; contrasts them with repeated customer reviews that could distort analysis.
- What you can do after
- Apply it via pandas `nunique()`, `value_counts()`, and `groupby()` to inspect distinct identifiers and repeated values.
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The Well-Grounded Rubyist, Fourth Edition
uniq is a Ruby Array method that returns a new array with duplicate elements removed according to equality comparison.
- How it is used
- Transforms an array into a new array with duplicate elements removed.
- How deep it goes
- Defines duplicates through pairwise == tests and notes uniq! as the in-place counterpart.
- Examples
- Demonstrates removing repeated integers from an array, yielding [1, 2, 3, 4, 5].
- What you can do after
- Apply Array#uniq to return a deduplicated array, or use uniq! to remove duplicates from the original.
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Statistics Slam Dunk
The unique() function in R returns the distinct elements, rows, or combinations of values in an object.
- How it is used
- Removes duplicate rows during NBA data wrangling before filtering and further analysis.
- How deep it goes
- Explains why rows duplicate, applies unique(), and verifies dimensions, but does not detail the function’s internal algorithm.
- Examples
- Uses NBAboxscores records duplicated by officials and checks reduction from 44,284 rows to 14,758.
- What you can do after
- Apply unique() to remove duplicate records and verify the cleaned data’s dimensions with dim().
Related concepts
- setaddressed by · A set is a collection of unique elements in which membership is determined by whether an element is present, not by duplicate occurrences.
- data frameused by · A data frame is a two-dimensional tabular data structure with labeled rows and columns that can contain values of different types.
- NumPyused by · NumPy is an open-source Python library for numerical computing that provides multidimensional arrays and operations on them.
- scopeconfigured by · Scope is a defined boundary specifying which entities, activities, resources, or conditions are included or governed in a particular context.
- comprehensionproduced by · A comprehension is a language construct that creates a collection by iterating over one or more sources, optionally filtering elements and transforming them.
- dropdownused by · A dropdown is a user-interface control that presents a set of choices for user selection, often revealing them when activated.
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