Datasets:

judicialmind
/

KCC-Pulse

---
license: cc-by-nc-sa-4.0
pretty_name: KCC-Pulse
language:
- en
task_categories:
- time-series-forecasting
tags:
- india
- agriculture
- kisan-call-centre
- pests
- crop-disease
- surveillance
- aggregates
- data.gov.in
size_categories:
- 1M<n<10M
configs:
- config_name: district_week_theme
  default: true
  data_files: panel/district_week_theme.parquet
- config_name: state_week
  data_files: panel/state_week.parquet
- config_name: series
  data_files: series/series.parquet
- config_name: forecasts
  data_files: forecasts/forecasts.parquet
extra_gated_prompt: 'This dataset is released under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 licence (CC BY-NC-SA 4.0): research, academic, personal and other non-commercial use is permitted with attribution; adaptations must be shared under the same licence; commercial use is not permitted. The original public source data remains under the Government Open Data License - India (GODL-India). Commercial use: contact surya@judicialmind.ai or hello@judicialmind.ai.'
extra_gated_fields:
  Name: text
  Email: text
  Organization: text
  I accept the CC BY-NC-SA licence terms (research and non-commercial use only): checkbox
extra_gated_button_content: Accept and request access
---
# KCC-Pulse

<!-- jm:top -->
Licence: CC BY-NC-SA 4.0 — research and non-commercial use only; derivatives must be shared under the same licence. Commercial use: contact surya@judicialmind.ai or hello@judicialmind.ai

Access is approved automatically when the email you enter matches your Hugging Face account email and belongs to the organisation you name; other requests are reviewed manually.
<!-- /jm:top -->

Weekly counts of Kisan Call Centre (KCC) calls per district and theme (pest, disease, weed, nutrient or intent),
for the 10 best-covered states, December 2009 to July 2025, with 1-4 week forecast backtests and surge alerts.
Aggregates only: no call text. A rise in calls about a pest or disease in a district is a signal of what farmers
are dealing with that week.

## Quickstart

The repository is gated: accept the terms on the dataset page, then `huggingface-cli login`.

```python
from datasets import load_dataset
panel = load_dataset("judicialmind/KCC-Pulse", "district_week_theme", split="train").to_pandas()
pests = panel[(panel.theme_kind == "entity") & (panel.state == "MAHARASHTRA")]
print(pests.groupby("theme")["calls"].sum().sort_values(ascending=False).head(10))
```

With pandas or DuckDB on a local copy (`huggingface-cli download judicialmind/KCC-Pulse --repo-type dataset
--local-dir KCC-Pulse`):

```python
import duckdb, pandas as pd
state = pd.read_parquet("KCC-Pulse/panel/state_week.parquet")
print(state[state.state == "PUNJAB"].tail(3))
print(duckdb.sql("""
    SELECT state, district, week, theme, calls
    FROM 'KCC-Pulse/panel/district_week_theme.parquet'
    WHERE theme = 'pest_control' AND calls IS NOT NULL
    ORDER BY calls DESC LIMIT 5
""").df())
```

Series for forecasting are in `series/series.parquet` (`series_id` = `STATE|DISTRICT|THEME`, weekly `ts`,
`target`); the evaluation origins and horizons are in `splits.json`.

## Files

| file | rows | contents |
|---|---|---|
| `panel/district_week_theme.parquet` | 3,854,625 | calls per district x ISO week (Monday) x theme |
| `panel/state_week.parquet` | 7,920 | all calls per state x week |
| `series/series.parquet` | 4,629,053 | 5,959 weekly district x theme series used for forecasting, with the PM-KISAN covariate |
| `forecasts/forecasts.parquet` | 200,000 | backtest forecasts (quantiles 0.1-0.9 and mean) with the observed value: seasonal naive for all six origins and Poisson GLM for the origins February-June 2025 |
| `forecasts/summary.json` | | forecast and alert scores per model (table below) |
| `splits.json` | | forecast cutoff, origins, horizons (1-4 weeks), season length (52) |
| `leadlag.json` | | cross-correlation between weekly calls about a crop and the weekly change in its mandi price, per district x crop |

## Schema

`panel/district_week_theme.parquet`

| column | type | description |
|---|---|---|
| `state`, `district` | string | as in the KCC records (upper case); `district` = `0` when the call has no district |
| `state_lgd`, `district_lgd` | int | LGD codes where the district name matched |
| `week` | date | ISO week start (Monday) |
| `theme` | string | the pest, disease, weed or nutrient named in the calls (`theme_kind` = `entity`, 40,999 names), else the call intent (`intent`: `weather`, `government_scheme`, `sowing_cultural`, `variety_seed`, `fertilizer_use`, `pest_control`, `nutrient_management`, `weed_management`, `market_price`, `disease_control`, `animal_husbandry`, `credit_insurance`, `irrigation_water`, `post_harvest`, `machinery`, `procurement_msp_complaint`, `other`, `unlabelled`) |
| `theme_kind` | string | `entity` or `intent` |
| `calls` | int | number of calls; null when suppressed |
| `calls_suppressed` | bool | true when the count was 1-9 |

`panel/state_week.parquet`: `state`, `week`, `state_calls`, `state_calls_suppressed`.

`series/series.parquet`: `series_id`, `ts` (week), `target` (calls; null = no calls logged in the state that
week, or suppressed), `target_suppressed`, `state`, `district`, `district_lgd`, `theme`,
`cov_pmkisan_beneficiaries` (PM-KISAN beneficiaries in the district for the installment covering the week).

`forecasts/forecasts.parquet`: `series_id`, `origin`, `h` (horizon, weeks), `model`, `ts`, `q0.1` ... `q0.9`,
`mean`, `y` (observed calls), `y_suppressed`.

A week is missing (null), not zero, when the state logged no calls at all that week. Small cells: published call
counts of 1-9 are null with `<column>_suppressed = true` (zeros are kept).

## Results

Forecasts of weekly calls per district and theme, 5,959 series, 6 origins (2025-02-17 to 2025-07-07), horizons 1-4
weeks, 27,870 windows per model (`forecasts/summary.json`):

| model | WQL | MASE | alert precision | alert recall |
|---|---|---|---|---|
| seasonal_naive | 1.103 | 0.559 | 0.10 | 0.05 |
| poisson_glm | 0.917 | 0.676 | 0.73 | 0.39 |
| chronos2 | 0.698 | 0.371 | 0.81 | 0.38 |

Alert = next-week calls more than 2x the seasonal baseline (same ISO week +-1 in the previous 3 years) and at least
10 calls. Forecast scores were computed on the unsuppressed counts.

## Coverage

10 best-covered states: Rajasthan, Maharashtra, Gujarat, Bihar, Punjab, Odisha, Karnataka, Haryana, Madhya
Pradesh, Himachal Pradesh; 356 district names (one per state is `0`, calls without a district); weeks from 2009-12-28 to 2025-07-28. The source holds 27,754,152 calls
from the public data.gov.in snapshot.

## Source data

Derived from 2 resources published on the Open Government Data Platform India (data.gov.in), snapshot May 2026, under the [Government Open Data License - India](https://data.gov.in/government-open-data-license-india).

Providers: Ministry of Agriculture and Farmers Welfare.

- Department of Agriculture and Farmers Welfare (Ministry of Agriculture and Farmers Welfare). "Kisan Call Centre (KCC) farmer queries". data.gov.in resource cef25fe2-9231-4128-8aec-2c948fedd43f, https://api.data.gov.in/resource/cef25fe2-9231-4128-8aec-2c948fedd43f. Licensed under the Government Open Data License - India (https://data.gov.in/government-open-data-license-india). Snapshot: May 2026.
- PM-KISAN village beneficiaries (resource 388208c6-d82a-4190-90df-91aa2c326fec) are joined as a covariate: Department of Agriculture and Farmers Welfare (Ministry of Agriculture and Farmers Welfare). "Village and Gender - wise Beneficiaries Count under PM - KISAN Scheme". data.gov.in resource 388208c6-d82a-4190-90df-91aa2c326fec, https://api.data.gov.in/resource/388208c6-d82a-4190-90df-91aa2c326fec.

<!-- jm:source -->
Original data: published by Department of Agriculture and Farmers Welfare, Ministry of Agriculture and Farmers Welfare (Kisan Call Centre; PM-KISAN) on the Open Government Data Platform India ([data.gov.in](https://data.gov.in)) and, where marked, NITI Aayog's National Data and Analytics Platform ([NDAP](https://ndap.niti.gov.in)), under the [Government Open Data License - India](https://data.gov.in/government-open-data-license-india) (GODL-India). The original public data remains under GODL-India; the CC BY-NC-SA 4.0 licence of this repository covers JudicialMind's compilation, derived fields, annotations, benchmarks and models.
<!-- /jm:source -->

## Citation

```bibtex
@misc{judicialmind2026kccpulse,
  title={KCC-Pulse: weekly Kisan Call Centre call counts by district and theme, with forecasts and surge alerts},
  author={JudicialMind},
  year={2026},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/datasets/judicialmind/KCC-Pulse}}
}
```

<!-- jm:license -->
## License

[CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) (see `LICENSE`): research, academic, personal and other non-commercial use, with attribution to JudicialMind and to the original data publishers; adaptations must be shared under the same licence. Commercial use requires a separate licence.

Commercial use: contact surya@judicialmind.ai or hello@judicialmind.ai.
<!-- /jm:license -->

	---
	license: cc-by-nc-sa-4.0
	pretty_name: KCC-Pulse
	language:
	- en
	task_categories:
	- time-series-forecasting
	tags:
	- india
	- agriculture
	- kisan-call-centre
	- pests
	- crop-disease
	- surveillance
	- aggregates
	- data.gov.in
	size_categories:
	- 1M<n<10M
	configs:
	- config_name: district_week_theme
	default: true
	data_files: panel/district_week_theme.parquet
	- config_name: state_week
	data_files: panel/state_week.parquet
	- config_name: series
	data_files: series/series.parquet
	- config_name: forecasts
	data_files: forecasts/forecasts.parquet
	extra_gated_prompt: 'This dataset is released under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 licence (CC BY-NC-SA 4.0): research, academic, personal and other non-commercial use is permitted with attribution; adaptations must be shared under the same licence; commercial use is not permitted. The original public source data remains under the Government Open Data License - India (GODL-India). Commercial use: contact surya@judicialmind.ai or hello@judicialmind.ai.'
	extra_gated_fields:
	Name: text
	Email: text
	Organization: text
	I accept the CC BY-NC-SA licence terms (research and non-commercial use only): checkbox
	extra_gated_button_content: Accept and request access
	---

	# KCC-Pulse

	<!-- jm:top -->
	Licence: CC BY-NC-SA 4.0 — research and non-commercial use only; derivatives must be shared under the same licence. Commercial use: contact surya@judicialmind.ai or hello@judicialmind.ai

	Access is approved automatically when the email you enter matches your Hugging Face account email and belongs to the organisation you name; other requests are reviewed manually.
	<!-- /jm:top -->

	Weekly counts of Kisan Call Centre (KCC) calls per district and theme (pest, disease, weed, nutrient or intent),
	for the 10 best-covered states, December 2009 to July 2025, with 1-4 week forecast backtests and surge alerts.
	Aggregates only: no call text. A rise in calls about a pest or disease in a district is a signal of what farmers
	are dealing with that week.

	## Quickstart

	The repository is gated: accept the terms on the dataset page, then `huggingface-cli login`.

	```python
	from datasets import load_dataset

	panel = load_dataset("judicialmind/KCC-Pulse", "district_week_theme", split="train").to_pandas()
	pests = panel[(panel.theme_kind == "entity") & (panel.state == "MAHARASHTRA")]
	print(pests.groupby("theme")["calls"].sum().sort_values(ascending=False).head(10))
	```

	With pandas or DuckDB on a local copy (`huggingface-cli download judicialmind/KCC-Pulse --repo-type dataset
	--local-dir KCC-Pulse`):

	```python
	import duckdb, pandas as pd

	state = pd.read_parquet("KCC-Pulse/panel/state_week.parquet")
	print(state[state.state == "PUNJAB"].tail(3))

	print(duckdb.sql("""
	SELECT state, district, week, theme, calls
	FROM 'KCC-Pulse/panel/district_week_theme.parquet'
	WHERE theme = 'pest_control' AND calls IS NOT NULL
	ORDER BY calls DESC LIMIT 5
	""").df())
	```

	Series for forecasting are in `series/series.parquet` (`series_id` = `STATE\|DISTRICT\|THEME`, weekly `ts`,
	`target`); the evaluation origins and horizons are in `splits.json`.

	## Files

	\| file \| rows \| contents \|
	\|---\|---\|---\|
	\| `panel/district_week_theme.parquet` \| 3,854,625 \| calls per district x ISO week (Monday) x theme \|
	\| `panel/state_week.parquet` \| 7,920 \| all calls per state x week \|
	\| `series/series.parquet` \| 4,629,053 \| 5,959 weekly district x theme series used for forecasting, with the PM-KISAN covariate \|
	\| `forecasts/forecasts.parquet` \| 200,000 \| backtest forecasts (quantiles 0.1-0.9 and mean) with the observed value: seasonal naive for all six origins and Poisson GLM for the origins February-June 2025 \|
	\| `forecasts/summary.json` \| \| forecast and alert scores per model (table below) \|
	\| `splits.json` \| \| forecast cutoff, origins, horizons (1-4 weeks), season length (52) \|
	\| `leadlag.json` \| \| cross-correlation between weekly calls about a crop and the weekly change in its mandi price, per district x crop \|

	## Schema

	`panel/district_week_theme.parquet`

	\| column \| type \| description \|
	\|---\|---\|---\|
	\| `state`, `district` \| string \| as in the KCC records (upper case); `district` = `0` when the call has no district \|
	\| `state_lgd`, `district_lgd` \| int \| LGD codes where the district name matched \|
	\| `week` \| date \| ISO week start (Monday) \|
	\| `theme` \| string \| the pest, disease, weed or nutrient named in the calls (`theme_kind` = `entity`, 40,999 names), else the call intent (`intent`: `weather`, `government_scheme`, `sowing_cultural`, `variety_seed`, `fertilizer_use`, `pest_control`, `nutrient_management`, `weed_management`, `market_price`, `disease_control`, `animal_husbandry`, `credit_insurance`, `irrigation_water`, `post_harvest`, `machinery`, `procurement_msp_complaint`, `other`, `unlabelled`) \|
	\| `theme_kind` \| string \| `entity` or `intent` \|
	\| `calls` \| int \| number of calls; null when suppressed \|
	\| `calls_suppressed` \| bool \| true when the count was 1-9 \|

	`panel/state_week.parquet`: `state`, `week`, `state_calls`, `state_calls_suppressed`.

	`series/series.parquet`: `series_id`, `ts` (week), `target` (calls; null = no calls logged in the state that
	week, or suppressed), `target_suppressed`, `state`, `district`, `district_lgd`, `theme`,
	`cov_pmkisan_beneficiaries` (PM-KISAN beneficiaries in the district for the installment covering the week).

	`forecasts/forecasts.parquet`: `series_id`, `origin`, `h` (horizon, weeks), `model`, `ts`, `q0.1` ... `q0.9`,
	`mean`, `y` (observed calls), `y_suppressed`.

	A week is missing (null), not zero, when the state logged no calls at all that week. Small cells: published call
	counts of 1-9 are null with `<column>_suppressed = true` (zeros are kept).

	## Results

	Forecasts of weekly calls per district and theme, 5,959 series, 6 origins (2025-02-17 to 2025-07-07), horizons 1-4
	weeks, 27,870 windows per model (`forecasts/summary.json`):

	\| model \| WQL \| MASE \| alert precision \| alert recall \|
	\|---\|---\|---\|---\|---\|
	\| seasonal_naive \| 1.103 \| 0.559 \| 0.10 \| 0.05 \|
	\| poisson_glm \| 0.917 \| 0.676 \| 0.73 \| 0.39 \|
	\| chronos2 \| 0.698 \| 0.371 \| 0.81 \| 0.38 \|

	Alert = next-week calls more than 2x the seasonal baseline (same ISO week +-1 in the previous 3 years) and at least
	10 calls. Forecast scores were computed on the unsuppressed counts.

	## Coverage

	10 best-covered states: Rajasthan, Maharashtra, Gujarat, Bihar, Punjab, Odisha, Karnataka, Haryana, Madhya
	Pradesh, Himachal Pradesh; 356 district names (one per state is `0`, calls without a district); weeks from 2009-12-28 to 2025-07-28. The source holds 27,754,152 calls
	from the public data.gov.in snapshot.

	## Source data

	Derived from 2 resources published on the Open Government Data Platform India (data.gov.in), snapshot May 2026, under the [Government Open Data License - India](https://data.gov.in/government-open-data-license-india).

	Providers: Ministry of Agriculture and Farmers Welfare.

	- Department of Agriculture and Farmers Welfare (Ministry of Agriculture and Farmers Welfare). "Kisan Call Centre (KCC) farmer queries". data.gov.in resource cef25fe2-9231-4128-8aec-2c948fedd43f, https://api.data.gov.in/resource/cef25fe2-9231-4128-8aec-2c948fedd43f. Licensed under the Government Open Data License - India (https://data.gov.in/government-open-data-license-india). Snapshot: May 2026.
	- PM-KISAN village beneficiaries (resource 388208c6-d82a-4190-90df-91aa2c326fec) are joined as a covariate: Department of Agriculture and Farmers Welfare (Ministry of Agriculture and Farmers Welfare). "Village and Gender - wise Beneficiaries Count under PM - KISAN Scheme". data.gov.in resource 388208c6-d82a-4190-90df-91aa2c326fec, https://api.data.gov.in/resource/388208c6-d82a-4190-90df-91aa2c326fec.

	<!-- jm:source -->
	Original data: published by Department of Agriculture and Farmers Welfare, Ministry of Agriculture and Farmers Welfare (Kisan Call Centre; PM-KISAN) on the Open Government Data Platform India ([data.gov.in](https://data.gov.in)) and, where marked, NITI Aayog's National Data and Analytics Platform ([NDAP](https://ndap.niti.gov.in)), under the [Government Open Data License - India](https://data.gov.in/government-open-data-license-india) (GODL-India). The original public data remains under GODL-India; the CC BY-NC-SA 4.0 licence of this repository covers JudicialMind's compilation, derived fields, annotations, benchmarks and models.
	<!-- /jm:source -->

	## Citation

	```bibtex
	@misc{judicialmind2026kccpulse,
	title={KCC-Pulse: weekly Kisan Call Centre call counts by district and theme, with forecasts and surge alerts},
	author={JudicialMind},
	year={2026},
	publisher={Hugging Face},
	howpublished={\url{https://huggingface.co/datasets/judicialmind/KCC-Pulse}}
	}
	```

	<!-- jm:license -->
	## License

	[CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) (see `LICENSE`): research, academic, personal and other non-commercial use, with attribution to JudicialMind and to the original data publishers; adaptations must be shared under the same licence. Commercial use requires a separate licence.

	Commercial use: contact surya@judicialmind.ai or hello@judicialmind.ai.
	<!-- /jm:license -->