The WordLens-Project
  • The WordLens-Project
  • Course Overview
  • Part 1: Transform and Visualize Data
    • 1 Working Environment
    • 2 R and the Tidyverse
    • 3 Data Loading
      • Tabular Data
      • Tidy Data
      • Exploring New Data
    • 4 Data Transformation
      • Select Columns
      • Filter Rows
      • Sort Rows
      • Add Or Change Columns
        • Calculate New Columns
        • Change Data Types
        • Rename Columns
        • Joining Data Sets
      • Summarize Rows
    • 5 Data Visualization
      • Pleas for Visualization
      • Fast and Simple Plots
      • Grammar of Graphics
  • Part 2: Rule-Based NLP
    • 6 Unstructured Data
    • 7 Searching Text
    • 8 Tokenizing Text
      • Filter or Sample Data
      • Clean and Normalize Text
      • Split Text Into Tokens
      • Removing Stop Words
      • Enrich Tokens
    • 9 Topic Classification
      • Deductive
      • Inductive
    • 10 Sentiment Analysis
    • 11 Text Classification
    • 12 Word Pairs and N-Grams
  • Part 3: NLP with Machine Learning
    • 13 Text Embeddings
    • 14 Part-Of-Speech
    • 15 Named Entities
    • 16 Syntactic Dependency
    • 17 Similarity
    • 18 Sentiment
    • 19 Text Classification
    • 20 Transformers
    • 21 Training a Model
    • 22 Large Language Models
  • Appendix
  • Resources
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  1. Part 1: Transform and Visualize Data
  2. 4 Data Transformation

Filter Rows

In this lesson, you'll learn how to reduce the rows in a data set to keep only those of interest.

PreviousSelect ColumnsNextSort Rows

Last updated 2 years ago

This lesson is coming soon. In the meantime, refer to the as well as from the book "R for Data Science" (2nd edition).

provided code examples on GitHub
the chapter on data transformation
Filtering rows reduces the vertical size of a data frame.
Drawing