This example illustrates how you can apply functions to generate random numeric data in your dataset. |

**Functions**:

**Source:**

In the following example, a company produces 10 circular parts, the size of which is measured in each product's radius in inches.

prodId | radius_in |
---|---|

p001 | 1 |

p002 | 2 |

p003 | 3 |

p004 | 4 |

p005 | 5 |

p006 | 6 |

p007 | 7 |

p008 | 8 |

p009 | 9 |

p010 | 10 |

Based on the above data, the company wants to generate some additional sizing information for these circular parts, including the generation of two points along each part's circumference where quality stress tests can be applied.

**Transformation:**

To begin, you can use the following steps to generate the area and circumference for each product, rounded to three decimal points:

For quality purposes, the company needs two tests points along the circumference, which are generated by calculating two separate random locations along the circumference. Since the `RANDBETWEEN`

function only calculates using Integer values, you must first truncate the values from `circumference_in`

:

Then, you can calculate the random points using the following:

**Results:**

After the `trunc_circumference_in`

column is dropped, the data should look similar to the following:

prodId | radius_in | area_sq_in | circumference_in | testPt01_in | testPt02_in |
---|---|---|---|---|---|

p001 | 1 | 3.142 | 6.283 | 5 | 5 |

p002 | 2 | 12.566 | 12.566 | 3 | 3 |

p003 | 3 | 28.274 | 18.850 | 13 | 13 |

p004 | 4 | 50.265 | 25.133 | 24 | 24 |

p005 | 5 | 78.540 | 31.416 | 0 | 0 |

p006 | 6 | 113.097 | 37.699 | 15 | 15 |

p007 | 7 | 153.938 | 43.982 | 11 | 11 |

p008 | 8 | 201.062 | 50.265 | 1 | 1 |

p009 | 9 | 254.469 | 56.549 | 29 | 29 |

p010 | 10 | 314.159 | 62.832 | 21 | 21 |