semvec/pypi-packages huggingface dataset:
dbcalc 0.1.4
A dB <-> power calculator for the command line

dbcalc
======

Conversion tool to do power <-> dB calculations. PARAMS is a list of space-separated values depending
on the mode (``i``, ``o`` or ``d``) selected.

* ``i`` — calculate input power from the PARAMS output power and dB
* ``o`` — calculate output power from the PARAMS input power and dB
* ``d`` — calculate dB from the PARAMS output power and input power

E.g.: to calculate the output power, given 1W of input power and 3dB loss

.. code:: sh

    $ dbcalc o 1 -3
    0.5011872336272722

Notice that the result has a newline character appended.
MLData 2.0.0
MLData is used to clean data before machine learning process!

#MLData
MLData, is a project to clean and normalize data for machine learning process.


## How to install
```pip install mldata```




## Usage Example
Usage Example:    
```
        from mldata import Processor
        new_file_path = "outputs/new.csv"
        processor = Processor("resource/raw_dataset.csv", target_column="APPROVE/NOT", exclude_column_list=["id"],
                              category_list=["Work Class", "FnlWgt", "Education", "Maried Status", "Occupation",
                                             "Relationship", "Race", "Gender", "Native Country", "Flag"],
                              invalid_values=["?", "", "null", None],
                              positive_tag=1)
        processor.normalize()
        processor.save_to_file(new_file_path)
```


## API Description    
1, Init function
```
Processor(csv_file_path, target_column, exclude_column_list=None, category_list=None, positive_tag=1,
                 csv_header=0, invalid_values=None)

```
Parameters:     
csv_file_path: The origin csv file path                
target_column: The column name of the target              
exclude_column_list: Columns no need to normalize       
category_list: A column name list which are category based columns       
positive_tag: The positive tag for the target column value, default value is 1        
invalid_values: values in csv not valid, such as "?", "", "null", None     

2, Norm the list
```buildoutcfg
Processor.normalize()   
``` 
This function is used to do norm to the csv file.


3, Save result to csv file.    
```buildoutcfg
Processor.save_to_file(new_file_name)          
``` 
This function is used to save normalized output to csv file.            
Parameters: 
new_file_name: The new file name to save the normalized data
python-module-starter 1.0.0
This package creates a framework for python packages to be built.

# pypi starter project

[![Build Status](https://travis-ci.org/wuhaifengdhu/python-module-starter.svg?branch=master)](https://travis-ci.org/wuhaifengdhu/python-module-starter)
[![codecov](https://codecov.io/gh/wuhaifengdhu/python-module-starter/branch/master/graph/badge.svg)](https://codecov.io/gh/wuhaifengdhu/python-module-starter)

This is a template repository that you can use to quickly create a python application that can be built, tested, and released as an internal python module.

## Setting up a new repository from this template
**Create a directory and pull all the files in this template into it**

```bash
mkdir new_repo_name
cd new_repo_name
git init
git pull https://github.com/wuhaifengdhu/python-module-starter.git
```

## Build

*Linux*

```bash
virtualenv env
. env/bin/activate
pip install -e .
```

*Windows*
```bash
virtualenv env
env\Scripts\activate
pip install -e .
```

## Tox Tests and Build the Wheels

```
pip install -r requirements-build.txt
# run the python tests
tox -r
```

## upload to pypi
* Register your account in ![pypi](https://pypi.org/)
* Create file .pypirc in your home folder with 600.    
```[distutils]
index-servers =
  pypi
  pypitest

[pypi]
repository=https://upload.pypi.org/legacy/
username=your_username
password=your_password

[pypitest]
repository=https://test.pypi.org/legacy/
username=your_username
password=your_password
``` 
* Upload your repository
```
python setup.py bdist_wheel --universal
twine upload dist/*
```