semvec/pypi-packages huggingface dataset:
nh3pred 0.1.3
Predict ammonia emissions with a recurrent neural network model
Requires Python: >=3.12.3

# nh3pred

This package provides a single function, `predict`, which estimates ammonia emissions following field fertilization under given environmental conditions.  
The underlying model is a recurrent neural network described in [ref] under the name *"rnn 9 – data a."*.  
The `predict` function works similarly to the `alfam2` function from the R package [ALFAM2](https://cran.r-project.org/web/packages/ALFAM2/index.html).

## Install

```bash
pip install nh3pred 
```

## Documentation

A complete documentation for the `predict` function is available [here](https://nh3pred.readthedocs.io/en/latest/api.html#nh3pred.api.predict).

## Usage

You can use the package in Python as follows:

```python
import pandas as pd
from nh3pred import predict

df = pd.DataFrame ({
    "pmid": [1, 1, 1, 1, 1, 1],
    "ct": [3, 6, 10, 24, 48, 72],
    "tan_app": [42, 42, 42, 42, 42, 42],
    "air_temp": [18, 23, 24, 15, 21, 20],
    "wind_2m": [2, 2, 1, 1, 2, 2],
    "rain_rate": 0,
    "app_rate": [20, 20, 20, 20, 20, 20],
    "man_dm": [8.3, 8.3, 8.3, 8.3, 8.3, 8.3],
    "man_ph": [7.1, 7.1, 7.1, 7.1, 7.1, 7.1],
    "app_mthd": ["ts", "ts", "ts", "ts", "ts", "ts"],
    "man_source": ["cat", "cat", "cat", "cat", "cat", "cat"]
})

pred = predict(df)
print(pred)
``` 


## Notes

- The trained weights are included in the package under `nh3pred/data/final_model.pth`.
- The package requires **Python ≥3.12**, **PyTorch ≥2.5.0**, and **pandas ≥2.2.3**.
pandas-datavalidation 1.0.0
A simple survey data validation package using pandas.
Requires Python: >=3.8

# pandas-validator


A Python library to validate survey and structured datasets using pandas.


## Installation
```bash
pip install pandas-validator
```


## Example
```python
from pandas-validator import SR, MULTI, initial_setup


df = initial_setup('survey_data.sav')
SR(Rout='QFILTER', QVAR='Q1', RNG=[1,2,3,4], LIST=['CID','Q1'])
```