Examples

Below are a few simple examples of what you can do with YuCalc.

Have an idea for YuCalc that you don’t see below? We’d love to hear from you – please contact us today!

analysis

sales analysis

Calculate Year-On-Year movements in sales by staff member or by product.

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Info:

  • Data source(s): Sales data (csv)
  • Models (tabs): 3
  • Complexity: Easy

About:

This workspace takes a set of sales records, including the date,product sold, amount and the sales person.

Using a variable to identify the financial year end, each record (sale) is allocated to the current or prior year. Additional models (tabs) then calculate aggreagate sales for the current and prior year, by salesperson and by product.

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mini

data mapping

Transform data using a “source” and “target model(tab) and using formulas to modify the content of each column.”

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Info:

  • Data source(s): Policy data (csv)
  • Models (tabs): 2
  • Complexity: Easy

About:

This workspace collects, maps and transforms some life insurance policy data.

Data is first fed into the “Source” model (tab). The “Target” model then contains formulas to first replicate the unique “Reference” number for each row and then return a transformed version of each column.

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senti

sentiment analysis

Score the sentiment of tweets using data from Twitter and a table of posistive and negative words .

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Info:

  • Data source(s): Tweets (from Twitter), list of positive and negative words (csv)
  • Models (tabs): 4
  • Complexity: Easy

About:

This workspace determines the sentiment of tweets using a lookup of positive and negative words.

A list of tweets are fed into the “Tweets” model (tab). A list of positive and negative words are also added to the workspace (each in their own model / tab). Each tweet is scored for sentiment and then the overall results are summarised by month.

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senti

Share trading strategy

A simple trading model that uses share price data and the moving average to identify buying and selling opportunities

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Info:

  • Data source(s): Share price data (csv)
  • Models (tabs): 3
  • Complexity: Medium

About:

This workspace takes a set of share prices, extracted from Yahoo Finance.

It then calculates the moving average and indicates a “buy” signal when the closing share price crosses above the moving average and a “sell” signal when the opposite occurs. Results are summarised including an analysis of overall profit vs the movement of the share price over the same period.

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