Feature Description
Implement support for ECDF (Empirical Cumulative Distribution Function) plots in PlotSense to expand plot type coverage and improve distribution analysis capabilities.
Problem Statement
Currently, PlotSense does not support ECDF plots, which limits users' ability to visualize cumulative distributions and understand percentiles or data spread effectively. Users must rely on external tools for this type of analysis.
Proposed Solution
Add ECDF as a supported plot type within the PlotGenerator and integrate it into the recommendation system.
Example Usage:
# How you envision using this feature
import plotsense as ps
# Your proposed API/usage
fig = ps.plotgen(df, suggestion={"plot_type": "ecdf", "variables": "age"})
# Optional grouped ECDF
fig = ps.plotgen(df, suggestion={"plot_type": "ecdf", "variables": "age, gender"})
Alternatives Considered
- Using histograms or KDE plots alone (do not provide cumulative insight)
- Relying on external libraries/tools (breaks PlotSense workflow consistency)
Benefits
-
For Data Scientists:
- Enables clear visualization of cumulative distributions and percentiles
- Complements existing KDE and histogram plots
-
For Analysts:
- Easier interpretation of thresholds (e.g., proportion below a value)
- Better decision-making support
-
For the Project:
- Expands supported plot types
- Improves recommendation engine capabilities
- Aligns with standard statistical visualization practices
Implementation Ideas
Affected Components:
Potential Challenges:
- Handling large datasets efficiently
- Supporting grouped ECDF cleanly
- Maintaining consistency with existing plot APIs
Mockups/Examples
Example using seaborn:
import seaborn as sns
sns.ecdfplot(data=df, x="age")
Additional Context
ECDF plots are widely used in statistical analysis and provide complementary insights to existing distribution plots such as histograms and KDE.
Would you like to work on this?
Related Features/Issues
Related to # (KDE plot issue)
Checklist
Feature Description
Implement support for ECDF (Empirical Cumulative Distribution Function) plots in PlotSense to expand plot type coverage and improve distribution analysis capabilities.
Problem Statement
Currently, PlotSense does not support ECDF plots, which limits users' ability to visualize cumulative distributions and understand percentiles or data spread effectively. Users must rely on external tools for this type of analysis.
Proposed Solution
Add ECDF as a supported plot type within the PlotGenerator and integrate it into the recommendation system.
Example Usage:
Alternatives Considered
Benefits
For Data Scientists:
For Analysts:
For the Project:
Implementation Ideas
Affected Components:
Potential Challenges:
Mockups/Examples
Example using seaborn:
Additional Context
ECDF plots are widely used in statistical analysis and provide complementary insights to existing distribution plots such as histograms and KDE.
Would you like to work on this?
Related Features/Issues
Related to # (KDE plot issue)
Checklist