semvec/pypi-packages huggingface dataset:
yorbali 0.0.2
Yorbali package for general-purpose data-processing tools
Requires Python: >=3.6

# Yorbali package
## for general-purpose data-processing tools

### How to install

pip install yorbali

### How to upgrade

pip install yorbali --upgrade

### How to use

import yorbali
or
from yorbali import *

### Modules included

CreData(rec=100000, dys=1000, dst='01/01/2017', pof=1):
    Create a dataframe with rec number of records, spread over dys mumber of
    days starting from date dst, including pof percent of offsetting records.
    Two records are offsetting if they have same values for "item" fields;
    and positive "amounts" record is followed by negative "amounts" record.

GetOffs(dfr, cre, cvl, cdt):
    Identify offsetting records in dataframe dfr, with array cre of
    grouping fields, array cvl of amount fields, and date field cdt.

GroupDf(dfr, cgp, cvl):
    Run GroupBy on a datafarme dfr, for all possible combinations of fields
    specified in array cgp, and evaluate Sum for fields in array cvl.

HighCol(col, dct={"z":"white"}):
    Use this as an argument in dataframe.style.apply,
    to highlight columns specified by keys of dictionary dct.

FormDis(dfr, num=5):
    Format and display num number of rows of dataframe dfr,
    with float-type values in 2 decimals and yellow color.

### Version History

0.0.2 2020-08-30 Added CreData and GetOffs.
0.0.1 2020-08-29 Initial release. Included GroupDf and FormDis.
datacleanbot 0.91
automated data cleaning tool

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

# datacleanbot
Automated Data Cleaning Tool.
The main goal is to develop a Python tool ``datacleanbot`` such that:
    Given a random parsed raw dataset representing a supervised learning problem, the Python tool is capable of automatically identifying the potential issues and reporting the results and recommendations to the end-user in an effective way.

## Install

```sh
$ pip install datacleanbot
```

## QuickStart

### Install OpenML (version 0.9.0):

OpenML is used to easily import datasets and share models and experiments.

```sh
$ pip install openml
```

For Windows, you need to have C++ Compiler installed.

### Acquire data from OpenML:

    >>> import openml as oml
    >>> data = oml.datasets.get_dataset(id) # id: openml dataset id
    >>> X, y, categorical_indicator, features = data.get_data(target=data.default_target_attribute, dataset_format='array')
    >>> Xy = np.concatenate((X,y.reshape((y.shape[0],1))), axis=1)

### Autoclean data with datacleanbot:

    >>> import datacleanbot.dataclean as dc
    >>> Xy = dc.autoclean(Xy, data.name, features)


## Description

``datacleanbot`` is equipped with the following capabilities:
* Present an overview report of the given dataset
    * The most important features
    * Statistical information (e.g., mean, max, min)
    * Data types of features
* Clean common data problems in the raw dataset
    * Duplicated records
    * Inconsistent column names
    * **Missing values**
    * **Outliers**

The two aspects ``datacleanbot`` meaningfully automates are marked in bold.

## User's Guide

The user's guide can be found at [datacleanbot](https://datacleanbot.readthedocs.io/en/latest/).
xkcd-comics 0.0.1
A simple script for downloading all xkcd comics
Requires Python: >=3.6

# xkcd

[![Join the chat at https://gitter.im/xkcd-script/xkcd](https://badges.gitter.im/xkcd-script/xkcd.svg)](https://gitter.im/xkcd-script/xkcd?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)![GitHub repo size](https://img.shields.io/github/repo-size/brayo-pip/xkcd)![License](https://img.shields.io/github/license/brayo-pip/xkcd)

This is a script for downloading all the xkcd comics

## How to use the script

clone the repo

```console
$git clone https://xkcd.com/brayo-pip/xkcd.git
```

Run this code to install all the dependencies

```console
$cd xkcd
```

```console
$pip3 install -r requirements.txt
```

Then run the script.

```console
$python xkcd/download.py
```

## How this script is better than most of the other scripts

I can't say for sure that this is the best script for downloading xkcd comics there is,
but I can say it's one of the fastest. The script uses persistent http connections which I haven't yet seen in another xkcd script.
The script skips previously downloaded comics and skips non-image comics such as js-scripts, it however highlights you of this and provides you with a link should you wish to visit the site yourself and see the 'interactive comic'.

## Other technical features

The script maintains a continuity file so that it can 'recall' the last comic it downloaded.
It does updates the continuity file every 10 comics, I didn't want to update too often as this could be a bottleneck.
The continuity file is also updated during this 'sleep' session.

The script also has an amateur network congestion control, simply sleeps for 0.5 seconds for every 10 comics downloaded.This may be necessary once I introduce multi-threading.

## Upcoming features

I wish to introduce multi-threading so as to be able to fully utilize the a user's bandwidth. Requesting multiple comics simultaneously and writing them to disk/SSD simultaneously.