Visual Python Manual
  • Visual Python Manual
  • GETTING STARTED
    • Welcome to Visual Python
    • How to install
    • Installing FAQ
    • Official homepage
    • Link to Github
  • Data Analysis
    • 1. Import
    • 2. File
    • 3. Data Info
    • 4. Frame
      • 4-1. Frame - Edit
      • 4-2. Frame - Transform
      • 4-3. Frame - Sort
      • 4-4. Frame - Encoding
      • 4-5. Frame - Data Cleaning
    • 5. Subset
    • 6. Groupby
    • 7. Bind
    • 8. Reshape
  • Visualization
    • 1. Chart Style
    • 2. Pandas Plot
    • 3. Matplotlib
    • 4. Seaborn
    • 5. Plotly
    • 6. WordCloud
  • Statistics
    • 1. Prob. Distribution
    • 2. Descriptive Statistics
    • 3. Normality Test
    • 4. Equal Var. Test
    • 5. Correlation Analysis
    • 6. Reliability Analysis
    • 7. Chi-square Test
    • 8. Student's T-test
    • 9. ANOVA
    • 10. Factor Analysis
    • 11. Regression
    • 12. Logistic Regression
  • Machine Learning
    • 1. Data Sets
    • 2. Data Split
    • 3. Data Prep
    • 4. AutoML
    • 5. Regressor
    • 6. Classifier
    • 7. Clustering
    • 8. Dimension
    • 9. GridSearch
    • 10. Fit/Predict
    • 11. Model Info
    • 12. Evaluation
    • 13. Pipeline
    • 14. Save / Load
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Visual Python Manual

This manual introduces the basic usages and tips for using Visual Python.

NextWelcome to Visual Python

Last updated 9 months ago

Getting Started

Data Analysis

Visualization

Statistics

Machine Learning

Welcome to Visual Python
How to install
Installing FAQ
Import
File
Data Info
Frame
Subset
Groupby
Bind
Reshape
Chart Style
Pandas Plot
Matplotlib
Seaborn
Plotly
WordCloud
Prob.Distribution
Descriptive Statistics
Normality Test
Equal Var. Test
Correlation Analysis
Reliability Analysis
Chi-square Test
Student's T-Test
ANOVA
Factor Analysis
Regression
Logistic Regression
Data Sets
Data Split
Data Prep
AutoML
Regressor
Classifier
Clustering
Dimension
GridSearch
Fit/Predict
Model Info
Evaluation
Pipeline