Metadata-Version: 2.1
Name: GusPI
Version: 0.0.21
Summary: A Statistical Support package
Home-page: https://github.com/ygeszvain/GusPI
Author: Randy Geszvain
Author-email: ygeszvain@gmail.com
License: UNKNOWN
Description: ## GusPI
        A package to include statistical supports.
        
        Quick start
        
        ```
        $ python3 -m pip install -U plotly
        
        $ python3 -m pip install -U GusPI
        ```
        
        ## Demo notebook
        
        [demo](https://colab.research.google.com/drive/1gVJvFCDwf7DxeKtt_jSd5FuEKZSRkvTb)
        
        ## 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
        ```
        
        ### metrics
        
        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)
        
        ### graphs
        
        Read sales data from csv file and print out a lineplot of a product quantity sold.
        
        ```
        #Example
        
        #sales data from a csv file: salesData.csv
        #product number to perform analysis on: 22LS
        
        #print the lineplot
        suPy.lineplotQtyByMonth('salesData.csv','22LS')
        ```
        
        Read sales data from csv file and print out a lineplot of a product's total cost sold.
        
        ```
        #Example
        
        #sales data from a csv file: salesData.csv
        #product number to perform analysis on: 22LS
        
        #print the lineplot
        suPy.lineplotTotalCostByMonth('salesData.csv','22LS')
        ```
        
        Read sales data from csv file and print out a lineplot of a product's total sales.
        
        ```
        #Example
        
        #sales data from a csv file: salesData.csv
        #product number to perform analysis on: 22LS
        
        #print the lineplot
        suPy.lineplotTotalSalesByMonth('salesData.csv','22LS')
        ```
        
        Read sales data from csv file and print out a lineplot of a product's average cost.
        
        ```
        #Example
        
        #sales data from a csv file: salesData.csv
        #product number to perform analysis on: 22LS
        
        #print the lineplot
        suPy.lineplotAverageCostByMonth('salesData.csv','22LS')
        ```
        
        Read sales data from csv file and print out a lineplot of a product's average sales.
        
        ```
        #Example
        
        #sales data from a csv file: salesData.csv
        #product number to perform analysis on: 22LS
        
        #print the lineplot
        suPy.lineplotAverageSalesPriceByMonth('salesData.csv','22LS')
        ```
        
        Read sales data from csv file and calculate basic safty sock and reporder point.
        
        ```
        #Example
        
        #sales data from a csv file: salesData.csv
        #product number to perform analysis on: 12LS
        #safety days: 5
        #leadtime in days: 7
        
        #print the lineplot
        suPy.basicSafetyStock('SalesData.csv','12LS',5,7)
        ```
        
        Read sales data from csv file and calculate safty sock and reporder point.
        
        ```
        #Example
        
        #sales data from a csv file: salesData.csv
        #product number to perform analysis on: 12LS
        #service rate: 5
        #leadtime in days: 7
        
        #print the lineplot
        suPy.safetyStockwtServiceRate('SalesData.csv','12LS',0.95,7)
        ```
        
        ## GusPI.finPy
        
        ```
        from GusPI import finPy
        ```
        
        Read financial statements from csv file and print them out as a dataframe.
        
        ```
        #Example
        
        #balancesheet from a csv file: balance_sheet_yr.csv
        
        #print the statement in a dataframe
        finPy.printStatement('balance_sheet_yr.csv')
        ```
        
        Read financial statements from csv files and provide a single line chart for analysis.
        
        ```
        #Example
        
        #income statement from a csv file: income_statement_m.csv
        
        #print a single line chart
        finPy.lineplot('income_statement_m.csv','total_revenue')
        ```
        
        Read financial statements from csv files and provide multiple line charts for analysis.
        
        ```
        #Example
        
        #balancesheet from a csv file: balance_sheet_yr.csv
        
        #print multiple lineplots
        finPy.multilineplots('balance_sheet_yr.csv', '3 year BalanceSheet Graph')
        ```
        
        Read financial statements from csv files and provide a bullet chart for analysis.
        
        ```
        #Example
        
        #balancesheet from a csv file: balance_sheet_yr.csv
        
        #print financial metrics
        finPy.bulletChart('balance_sheet_yr.csv','inventory')
        ```
        
        Read financial statements from csv files and provide financial metrics for analysis.
        
        ```
        #Example
        
        #balancesheet from a csv file: balance_sheet_yr.csv
        #incomeStatement from a csv file: income_statement_3yr.csv
        
        #print financial metrics
        finPy.calculateMetrics('balance_sheet_yr.csv','income_statement_12m.csv')
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
