This project explores contraceptive method choice among married women in Indonesia using an interactive Power BI dashboard. It leverages demographic and socioeconomic data to uncover patterns in family planning behavior.
- Dataset: Contraceptive Method Choice Data Set
- Provider: UCI Machine Learning Repository
- Original Study: 1987 National Indonesia Contraceptive Prevalence Survey
- Sample: 1,473 married women who were not pregnant or unsure of their pregnancy status at the time of interview
- Target Variable: Current contraceptive method – No Use, Short-Term, or Long-Term
- Features: Wife and husband’s age, education, occupation, religion, number of children, working status, and media exposure
- Tracks contraceptive usage across working vs non-working women
- Measures modern contraceptive prevalence rate (mCPR), average number of children
- Shows relationships by religion, education, and media access
- Highlights how husband’s job type and education level influence method choice
- Uses heatmaps, treemaps, bar charts, and line graphs
- Analyzes average number of children across occupational and educational groups
- mCPR (Modern Contraceptive Prevalence Rate): 57.30%
- Average Number of Children: 3.26
- Only 25% of women surveyed are working (369 out of 1,473)
- Couples where both spouses are highly educated show the highest contraceptive use and lowest average number of children
- Laborers and salesmen with low education levels are associated with higher fertility
- Professionals with high education prefer long-term contraceptive methods and have fewer children
- Working women tend to use short- and long-term methods more often
- Women with good media exposure show significantly higher contraceptive uptake
- 32.9% of women reported poor or no media access
- Power BI – Interactive dashboard, DAX measures, visual storytelling
- Python (Pandas) – Data preprocessing and transformation (see notebooks)
- DAX – For calculating KPIs like mCPR, average children, and working population count
Contraceptive-Use-Dashboard/
├── preprocessing.ipynb # Python notebook for data preparation
├── converting_file.ipynb # File transformation for Power BI
├── Contraceptive UIC Study.pbix # Power BI dashboard file
├── cmc_cleaned.csv
├── cmc_labeled.csv
├── cmc.data
├── cmc.db
├── cmc.names
└── README.md # Project documentation
This analysis shows that contraceptive behavior is strongly shaped by education, occupation, and access to media. The findings support policy interventions targeting low-educated, low-income couples and emphasize the importance of women’s empowerment and information access.
Sneha Dutt
B.S. in Computer Science & Accounting