Free Online Flashcard Deck

5. Cleaning and Preparing Datasets Free Online FlashCards

Study 5. Cleaning and Preparing Datasets with 12 free online flashcards. Review key terms, definitions, and concepts with this interactive flashcard deck.

12 cards
01
Front

What is a dataset?

Back

A dataset is an organized collection of observations, often stored as a spreadsheet, CSV file, database table, or specialized format such as Parquet.

02
Front

How do a field and a record differ?

Back

A field, or column, describes one characteristic; a record, or row, contains the values associated with one case, event, or entity.

03
Front

What does a data dictionary define?

Back

A data dictionary or schema records field meanings, expected types, units, permitted values, coding conventions, table relationships, intended use, and limitations.

04
Front

What makes an identifier a primary key?

Back

A primary key is an identifier with a unique value for each valid record. It distinguishes records but should not be treated as a meaningful measurement or ranking.

05
Front

Why preserve the raw dataset?

Back

Preserving raw data keeps an unchanged copy of the source file, allowing transformations to be traced, repeated, checked, or reversed.

06
Front

Why must missing values be distinguished from zero?

Back

A blank or missing value does not automatically mean zero. Zero may represent a measured quantity, whereas a blank may mean unavailable, inapplicable, withheld, or unrecorded.

07
Front

What is imputation?

Back

Imputation estimates a replacement value using a justified method, such as a group median or interpolation. The replacement remains an estimate, not an observed fact.

08
Front

What is the purpose of standardization?

Back

Standardization gives equivalent values one consistent representation, such as approved category codes or ISO dates, without erasing distinctions that carry meaning.

09
Front

What problem can duplicate records cause?

Back

A duplicate is an unnecessary repeated record, either exactly or through a repeated identifier. Duplicates can cause observations to be counted more than once.

10
Front

What is an outlier?

Back

An outlier is a value unusually far from most others. It may be an error, a unit mistake, a valid rare observation, or evidence of changed conditions.

11
Front

How should an outlier be handled?

Back

Outliers should be flagged and investigated against source records, domain limits, and context before removal. Valid rare observations may need to be retained.

12
Front

What does a range check test?

Back

A range check tests whether a value lies within a reasonable interval, such as 0 to 100 for a percentage or 0 to 1 for a probability.