Upload README.md with huggingface_hub

README.md

@@ -1,45 +1,102 @@
----
-dataset_info:
-  features:
-  - name: task_id
-    dtype: string
-  - name: task_name
-    dtype: string
-  - name: global_usage_count
-    dtype: float64
-  - name: global_usage_pct
-    dtype: float64
-  - name: automation_pct
-    dtype: float64
-  - name: augmentation_pct
-    dtype: float64
-  - name: dominant_collaboration_pattern
-    dtype: string
-  - name: dominant_pattern_pct
-    dtype: float64
-  - name: directive_pct
-    dtype: float64
-  - name: task_iteration_pct
-    dtype: float64
-  - name: learning_pct
-    dtype: float64
-  - name: feedback_loop_pct
-    dtype: float64
-  - name: validation_pct
-    dtype: float64
-  - name: india_usage_count
-    dtype: float64
-  - name: india_usage_pct
-    dtype: float64
-  splits:
-  - name: train
-    num_bytes: 607791
-    num_examples: 2616
-  download_size: 249691
-  dataset_size: 607791
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
----
+# Anthropic Economic Index - Structured Task Dataset
+
+## Dataset Description
+
+This dataset provides a structured, flattened view of the Anthropic Economic Index data, focusing on real-world AI task usage patterns, collaboration behaviors, and India-specific insights.
+
+**Source**: [Anthropic/EconomicIndex](https://huggingface.co/datasets/Anthropic/EconomicIndex)
+
+**Processing**: This dataset was extracted and structured from the raw Economic Index data using custom analysis scripts to provide:
+- Task-level usage metrics (global and India-specific)
+- Collaboration pattern distributions
+- Automation/augmentation percentages
+- Easy-to-use tabular format
+
+## Dataset Statistics
+
+- **Total Tasks**: 2,616
+- **Total Columns**: 15
+- **Tasks with India Data**: 47
+- **Total India Usage**: 40,693
+
+## Column Descriptions
+
+### Task Identification
+- `task_id`: Unique identifier for each task
+- `task_name`: Description of the task (from O*NET occupational tasks)
+
+### Usage Metrics (Global)
+- `global_usage_count`: Number of times this task was used globally
+- `global_usage_pct`: Percentage of total global usage this task represents
+
+### Automation & Augmentation
+- `automation_pct`: Percentage of usage involving full automation
+- `augmentation_pct`: Percentage of usage involving human-AI augmentation
+
+### Collaboration Patterns (Global)
+These show how users collaborate with Claude when performing this specific task:
+
+- `dominant_collaboration_pattern`: The most common collaboration pattern for this task
+- `dominant_pattern_pct`: Percentage of the dominant pattern
+- `directive_pct`: % of usage with directive pattern (user gives clear instructions)
+- `task_iteration_pct`: % of usage with iterative refinement pattern
+- `learning_pct`: % of usage where user is learning/exploring
+- `feedback_loop_pct`: % of usage with back-and-forth feedback
+- `validation_pct`: % of usage for validation/checking work
+
+### India-Specific Metrics
+- `india_usage_count`: Number of times this task was used in India
+- `india_usage_pct`: Percentage of total India usage this task represents
+
+## Use Cases
+
+This dataset is ideal for:
+
+1. **Understanding AI Task Patterns**: Analyze which real-world tasks are commonly performed with AI assistance
+2. **Persona-Task Matching**: Match AI usage patterns to user personas for scenario generation
+3. **Collaboration Research**: Study how different tasks require different human-AI collaboration patterns
+4. **Regional Analysis**: Compare global vs India-specific task usage patterns
+5. **Automation Research**: Understand which tasks are being automated vs augmented
+
+## Top Tasks by India Usage
+
+The most popular tasks in India include:
+1. Writing/modifying programs to meet customer requirements
+2. [Analysis of your data will reveal more patterns]
+
+## Citation
+
+If you use this dataset, please cite both this processed version and the original Economic Index:
+
+```
+@misc{economic_index_structured,
+  title={Anthropic Economic Index - Structured Task Dataset},
+  author={Sarvam AI},
+  year={2025},
+  howpublished={\url{https://huggingface.co/datasets/anna-sarvam/economic_index_structured}}
+}
+
+@misc{anthropic_economic_index,
+  title={Anthropic Economic Index},
+  author={Anthropic},
+  year={2025},
+  howpublished={\url{https://huggingface.co/datasets/Anthropic/EconomicIndex}}
+}
+```
+
+## Data Processing
+
+This dataset was created using a multi-step pipeline:
+1. Downloaded raw Economic Index CSV files from Anthropic's repository
+2. Extracted task information, collaboration patterns, and intersection data
+3. Calculated India-specific metrics from geo-filtered data
+4. Flattened into a single tabular format for easy analysis
+5. Removed redundant columns and kept only valuable metrics
+
+## License
+
+This dataset follows the same license as the original Anthropic Economic Index dataset.
+
+## Contact
+
+For questions or issues, please open an issue in the source repository.