Extrovert vs. Introvert Behavior Data
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Overview
Dive into the Extrovert vs. Introvert Personality Traits Dataset, a rich collection of behavioral and social data designed to explore the spectrum of human personality. This dataset captures key indicators of extroversion and introversion, making it a valuable resource for psychologists, data scientists, and researchers studying social behavior, personality prediction, or data preprocessing techniques.
Context
Personality traits like extroversion and introversion shape how individuals interact with their social environments. This dataset provides insights into behaviors such as time spent alone, social event attendance, and social media engagement, enabling applications in psychology, sociology, marketing, and machine learning. Whether you're predicting personality types or analyzing social patterns, this dataset is your gateway to uncovering fascinating insights.
Dataset Details
Size: The dataset contains 2,900 rows and 8 columns.
Features:
- Time_spent_Alone: Hours spent alone daily (0–11).
- Stage_fear: Presence of stage fright (Yes/No).
- Social_event_attendance: Frequency of social events (0–10).
- Going_outside: Frequency of going outside (0–7).
- Drained_after_socializing: Feeling drained after socializing (Yes/No).
- Friends_circle_size: Number of close friends (0–15).
- Post_frequency: Social media post frequency (0–10).
- Personality: Target variable (Extrovert/Introvert).*
Data Quality: Includes some missing values, ideal for practicing imputation and preprocessing.
Format: Single CSV file, compatible with Python, R, and other tools.*
Data Quality Notes
Contains missing values in columns like Time_spent_Alone and Going_outside, offering opportunities for data cleaning practice.
Balanced classes ensure robust model training.
Binary categorical variables simplify encoding tasks.
Potential Use Cases
Build machine learning models to predict personality types.
Analyze correlations between social behaviors and personality traits.
Explore social media engagement patterns.
Practice data preprocessing techniques like imputation and encoding.
Create visualizations to uncover behavioral trends.
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Original Data Source: Extrovert vs. Introvert Behavior Data