comrademonk/india-upi-ecosystem-2018-2025

---
pretty_name: India UPI Ecosystem (2018-2025)
language:
- en
license: cdla-permissive-2.0
task_categories:
- tabular-regression
- time-series-forecasting
task_ids:
- multivariate-time-series-forecasting
- tabular-single-column-regression
size_categories:
- 10K<n<100K
tags:
- upi
- india
- digital-payments
- finance
- analytics
---

# India UPI Ecosystem Dataset (2018-2025)

## Dataset Summary

This dataset analyzes India's UPI transaction ecosystem by combining district-level app and usage data, official NPCI benchmark statistics, and RBI macroeconomic cash indicators.
It is a merged and enriched analytics dataset designed for market concentration studies, geographic adoption analysis, forecasting, and cash displacement research.

## Data Sources

| Source | What it contains | Why it was used |
| ------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------ | ----------------------------------------------------------------------------------------------- |
| [PhonePe Pulse](https://github.com/PhonePe/pulse) | District-level UPI transactions, user registrations, and related app usage fields. Time period: Q1 2018 - Q2 2025. | Provides granular district-level coverage needed for regional adoption and inequality analysis. |
| [NPCI UPI Ecosystem Statistics](https://www.npci.org.in/what-we-do/upi/upi-ecosystem-statistics) | Official monthly UPI transaction volumes and app market-share values. Time period: Jan 2022 - Jun 2025. | Serves as official benchmark and ground-truth reference for national UPI trends and app shares. |
| [RBI DBIE](https://dbie.rbi.org.in) | Currency in circulation and ATM transaction volumes. Time period: Q1 2019 - Q2 2025. | Adds macroeconomic cash indicators required for digital-vs-cash displacement analysis. |

## Data Format & Usage

The final merged dataset is stored in `.parquet` format for efficient loading and analytics workflows.

```python
from datasets import load_dataset

# Load directly from Hugging Face
dataset = load_dataset("prasad-gade05/india-upi-ecosystem-2018-2025")
print(dataset)
```

## Acknowledgements & Attribution

This dataset is derived from:

- PhonePe Pulse
- National Payments Corporation of India (NPCI)
- Reserve Bank of India (RBI DBIE)

PhonePe Pulse data is governed by the **CDLA-Permissive-2.0** open data license, and this combined dataset is released under `cdla-permissive-2.0`.

pretty_name: 印度统一支付接口(UPI, Unified Payments Interface)生态系统（2018-2025）
language: 英语
license: CDLA-Permissive-2.0许可协议
task_categories:
- 表格回归
- 时间序列预测
task_ids:
- 多变量时间序列预测
- 单列表格回归
size_categories:
- 10K < n < 100K
tags:
- UPI
- 印度
- 数字支付
- 金融
- 数据分析

# 印度统一支付接口(UPI)生态系统数据集（2018-2025）

## 数据集概述
本数据集整合区级应用与使用数据、印度国家支付公司(NPCI, National Payments Corporation of India)官方基准统计数据以及印度储备银行(RBI, Reserve Bank of India)宏观经济现金指标，对印度统一支付接口(UPI)交易生态系统展开分析。
本数据集为经过整合与增强的分析型数据集，适用于市场集中度研究、地域普及分析、预测以及现金替代研究。

## 数据来源
| 数据来源 | 包含内容 | 使用原因 |
| --- | --- | --- |
| [PhonePe Pulse](https://github.com/PhonePe/pulse) | 区级UPI交易数据、用户注册量及相关应用使用字段，时间范围：2018年第一季度至2025年第二季度 | 可提供区域普及与不平等分析所需的精细区级覆盖范围 |
| [NPCI UPI生态系统统计数据](https://www.npci.org.in/what-we-do/upi/upi-ecosystem-statistics) | 官方月度UPI交易总量与应用市场份额数据，时间范围：2022年1月至2025年6月 | 可作为印度全国UPI趋势与应用份额的官方基准与真实参考依据 |
| [RBI DBIE数据库](https://dbie.rbi.org.in) | 流通中货币量与ATM交易总量，时间范围：2019年第一季度至2025年第二季度 | 可补充数字支付与现金替代研究所需的宏观经济现金指标 |

## 数据格式与使用说明
最终整合后的数据集以`.parquet`格式存储，可高效加载并用于分析工作流程。

python
from datasets import load_dataset

# 从Hugging Face直接加载数据集
dataset = load_dataset("prasad-gade05/india-upi-ecosystem-2018-2025")
print(dataset)

## 致谢与署名声明
本数据集源自以下来源：
- PhonePe Pulse
- 印度国家支付公司(NPCI, National Payments Corporation of India)
- 印度储备银行(RBI DBIE, Reserve Bank of India Database & Information Retrieval Environment)

PhonePe Pulse数据受**CDLA-Permissive-2.0**开放数据许可协议约束，本整合数据集亦以`cdla-permissive-2.0`协议发布。