semvec/pypi-packages huggingface dataset:
PrepDatosBD 0.8
This library aims to simplify and agilize the process of data preprocessing and cleaning, which is critical in any data analysis or machine learning project. By providing a variety of tools and functions, users can work more efficiently and ensure the quality of the data they are working with.
License: MIT
Keywords: Visualize,Preprocess,Read

# PrepDatosBD
## Read, Preprocess and Visualize your data

This library aims to simplify and agilize the process of data preprocessing and cleaning, which is critical in any data analysis or machine learning project. By providing a variety of tools and functions, users can work more efficiently and ensure the quality of the data they are working with.

## Required libraries
```sh
- import pandas as pd
- import matplotlib.pyplot as plt
- from sklearn.impute import KNNImputer
- import seaborn as sns
- import json
- import csv
- from openpyxl import load_workbook
- import xlrd
- from openpyxl.utils.exceptions import InvalidFileException
- import xml.etree.ElementTree as ET
- import numpy as np
```

## Available classes
## Initial class: Preprocess
This class is used to perform basic data processing by means of different specific functions.

*def describe_var(self, variables, tipo_var):*
> This method will be used to describe one or more columns from a dataframe. 
The description will be: Count, min, pct 25, mean, median, pct 75, max, std, NaN count and not NaN count.

*def view_nan_table(self):*
> This method is used to generate and view a NaN table. It contains the number of missing values and the percentage of them for each column.

*def drop_column(self, column_list):*
> This method will be used to drop one or more columns from a dataframe.

*def inplace_missings(self, column, method, n_neighbors=2):*
> This method inplaces missing values of a given table with the method wanted.

## Inherited class: ReadPreprocess
This inherited class is used to perform more advanced data processing by means of different specific functions.

*def file_to_dataframe(self, path):*
> This method will be used parse files from several extensions to a pandas dataframe.

*def outlier_detection(self, df, column_list=[]):*
> This method will be used to plot and detect outliers from one or more columns.

*def view_nan_graph(self, nan_table):*
> This method is used to graph the missing values of a dataframe.

## License

MIT

*Free Software, Hell Yeah!*
pyqanat 0.0.0
Create simple event-driven, distributed data pipelines in Python
License: MIT
Requires Python: >=3.11
Keywords: data pipelines event-driven architecture microservices mqtt

# Qanat

Qanat: Create simple event-driven, distributed data pipelines in Python.

Qanat is a lightweight tool for setting up event-driven, distributed data pipelines with
ease. It lets you link together components into a type-checked, decoupled pipeline, with
inter-process communication handled automatically through MQTT (in the future RabbitMQ?)
and serialization handled through JSON.

## Usage Example

```python
from qanat import QanatPipeline
from dataclasses import dataclass
from typing import List

@dataclass
class Frame:
    image: bytes
    timestamp: str

@dataclass
class Detection:
    type: str
    confidence: float

@dataclass
class DetectionResults:
    objects: List[Detection]
    frame_timestamp: str

# Initialize the pipeline with the MQTT broker connection
pipeline = QanatPipeline(broker="mqtt://broker.hivemq.com:1883")

@pipeline.component(output="qanat-demo/frames/raw")
def frame_producer() -> Frame:
    """
    Simulates producing a frame and its metadata.
    """
    image_data = b'some_image_data'  # Replace with actual image data
    return Frame(image=image_data, timestamp="2021-07-01T00:00:00Z")

@pipeline.component(
    input="qanat-demo/frames/raw", 
    output="qanat-demo/detections/results"
)
def detector(frame: Frame) -> DetectionResults:
    """
    Processes a frame and detects objects, outputting detection results.
    """
    detected_objects = [Detection(type="smoke", confidence=0.98)]
    return DetectionResults(objects=detected_objects, frame_timestamp=frame.timestamp)

@pipeline.component(input="qanat-demo/detections/results")
def result_publisher(detection_results: DetectionResults):
    """
    Publishes the detection results.
    """
    print(f"Publishing results: {detection_results}")

# Start the event loop for testing and demonstration
if __name__ == "__main__":
    # For demo or testing purposes, this runs all components in the pipeline
    pipeline.start_event_loop() # Blocks until the event loop terminates

    # In real-world distributed usage, you would start three separate processes, 
    # one for each component, e.g.:
    # frame_producer.start() # Blocks until this specific component terminates
```
pyprogramsimp 0.1.1
A simple package.
License: MIT

# pyprogramsimp
pyprogramsimp is a simple python package (still updating) that (until 0.1.1) provides basic calculations and opening documents.

## Installation
You can install pyprogramsimp using pip:

'''bash
pip install pyprogramsimp

## License
This project is lecensed under the MIT License

# Copyright (c) 2023 Ziyan Zhou
# 
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
# 
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
# 
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.