GusPI 0.0.13

A Statistical Support package

GusPI

A package to include statistical supports.

Quick start

$ python3 -m pip install -U GusPI

GusPI.scraper

The scrape package provides an easy way to scrape Yelp business info and Yelp reviews for specific business.

from GusPI import scraper

YelpBizInfo The function collects business info and save it into a csv file.

#Example

#declare a list: https://www.yelp.com/biz/`artisan-ramen-milwaukee`
CUISINES = ['artisan-ramen-milwaukee','red-light-ramen-milwaukee-5']

#scrape the business info
scraper.YelpBizInfo(CUISINES)

YelpReview The function collects reviews for respective business and save them into separate files by business names.

#Example

#declare a list: https://www.yelp.com/biz/`artisan-ramen-milwaukee`
CUISINES = ['artisan-ramen-milwaukee','red-light-ramen-milwaukee-5']

#scrape the business info
scraper.YelpReview(CUISINES)

GusPI.suPY

from GusPI import suPY

This package provides several analytical formulas to support supply chain analytics.

Economic order quantity EOQ(demand, mean, STD, C, Ce, Cs, Ct)

Perfect Order Measurement POM(TotalOrders, ErrorOrders)

Fill Rate FR(TotalItems, ShippedItems)

Inventory Days of Supply IDS(InventoryOnHand,AvgDailyUsage)

Freight cost per unit FCU(TotalFreightCost,NumberOfItems)

Inventory Turnover IT(COGS,AvgInventory)

Days of Supply (DOS) DOS(AvgInventory,MonthlyDemand)

Gross Margin Return on Investment (GMROI) GMROI(GrossProfit, OpeningStock, ClosingStock)

Inventory Accuracy IA(ItemCounts, TotalItemCounts)

Storage Utilization Rate SUR(InventoryCube, TotalWarehouseCube)

Total Order Cycle Time TOCT(TimeOrderReceivedbyCustomer, TimeOrderPlaced,TotalNumberofOrdersShipped)

Internal Order Cycle Time IOCT(TimeOrderShipped, TimeOrderReceived, NumberofOrdersShipped)

GusPI.finPy

from GusPI import finPy

Read financial statements from csv file and print them out as a dataframe.

#Example

#A balancesheet from a csv file: balance_sheet_3yr.csv

#print the statement in a dataframe
finPy.printStatement('balance_sheet_3yr.csv')

Read financial statements from csv files and provide multiple line charts for analysis.

#Example

#A balancesheet from a csv file: income_statement_12m.csv

#print multiple multiple line charts
finPy.multiLinecharts('income_statement_12m.csv')