R-Flow
  • R-Flow Task Guide
  • User-Guide
  • R
    • Transfer: R to Python
    • Script: R Script
    • Data Preprocess
      • Data Cleansing (Missing, Duplicate Data)
        • Missing Data Imputer
        • Outlier Imputer
      • Data Scaler
      • Normalize
      • Encode Feature
      • Highly Imbalanced Data
      • Data Handling
        • Data Aggregate
        • Data Subset
        • Data Filter
        • Data Join
        • Data Merge
        • Data Sort
        • Data Sampling
        • Data Imputation
    • Statistics
      • Hypothesis Test
      • ANOVA
      • PCR
      • Time Series Analysis
      • Factor Analysis
    • Machine Learning
      • Feature Selection
        • Filter Methods
        • Wrapper Methods
      • Dimension Reduction
      • Neural Network based ML
      • Similarity based ML
      • Information based ML
      • Bayesian Based ML
      • Clustering
        • Optimal
        • OPTICS
        • Others
      • Outlier Detection
        • Univariate Outliers
        • Bivariate Outliers
        • Multivariate Outliers
        • Time-Series Outliers
      • Recommend
      • Association Rule Analysis
    • Data Predict
    • R Object Load, Save
  • Python
    • Transfer: Python To R
    • Script: Python Script
    • Data Preprocess
      • Data Cleansing
        • Missing Data Imputer
      • Data Scaler
      • Normalize
      • Encode Feature
      • Highly-Imbalanced Data
        • Under-Sampling
        • Over-Sampling
        • Combination of over- and under-sampling
      • Data Handling
        • Data Aggregate
        • Data X,Y Split
        • Data Filter
        • Data Join
        • Data Concat
        • Data Sampling
        • Data Imputation
    • Machine Learning
      • Estimator
      • Probability Calibration
      • Clustering
      • Matrix Decomposition
      • Discriminant Analysis
      • Ensemble Methods
      • Feature Selection
      • Isotonic regression
      • Kernel Ridge Regression
      • Linear Models
        • Linear classifiers
        • Classical linear regressors
        • Regressors with variable selection
        • Bayesian Reg.
        • Multi-task linear regressors with variable selection
        • Outlier-robust regressors
      • Manifold Learning
      • Gaussian Mixture Models
      • Model Selection
      • Multiclass and Multilabel Classification
      • Multioutput regression and classification
      • Naive Bayes
      • Nearest Neighbors
      • Neural network models
      • Support Vector Machines
    • Data Predict/Transform
      • Data Transform
      • Python Predict
    • Python Object Load,Save
Powered by GitBook
On this page
  • Data Filter
  • Input Data
  • Workflow Example
  • R Pacakges

Was this helpful?

  1. R
  2. Data Preprocess
  3. Data Handling

Data Filter

PreviousData SubsetNextData Join

Last updated 3 years ago

Was this helpful?

Data Filter

Input Data

Target Data

Input Data

Output Name

Output data frame name after filtering

Filter Condition

Conditions for the filter

Add Logical Cond. creates a logical condition(and, or). Drag the variable name to the filter condition area.

Another way to add the variables is to click Add Filter Item and type the variable name manually.

Workflow Example

R-Flow Task Example Video - Data Filter

R Pacakges

Data Filter: https://cran.r-project.org/web/packages/dplyr/index.html

[Task Information of Data Filter]