Skip to main content

Compare data in source sheet with target sheet and copy missing rows to target sheet with Google Apps Script

Source sheet has 8 columns and target sheet has 9 columns (note first 8 columns are the same, the 9th column is used to set a url link once it has been mailed out). I don't want the target sheet to be sorted. The url link has to be on the appropriate row it pertains to.

This is the code I am working with so far. It does pull and compare the data, but it keeps adding a blank row at the beginning and after each run. I can't figure out why it does that?

function addNewStudents() {

  let ss = SpreadsheetApp.getActiveSpreadsheet()
  let source = ss.getSheetByName('Accepted Students')

  let sourceValues = source.getRange(2, 1, source.getLastRow(), 8).getValues().filter(String)
  //sourceValues.shift()
  //Logger.log(sourceValues)

  let targetSheet = ss.getSheetByName('Confirmation Letters')
  let targetValues = targetSheet.getRange(2, 1, targetSheet.getLastRow(), 8).getValues().filter(String)

  //console.log(targetValues)

  let diff = targetValues.showDif(sourceValues)


  targetValues = (diff.length && diff) ? targetValues.concat(diff) : targetValues
  // console.log(targetValues)
  if (targetValues === '') {
    var ui = SpreadsheetApp.getUi()
    ui.alert("No new students")

  } else {
    targetSheet.getRange(2, 1, targetValues.length, targetValues[0].length).setValues(targetValues)
  }
  //console.log(targetValues.length)
}

Array.prototype.showDif = function (array) {
  let that = this;
  return array.filter(function (r) {
    return !that.some(function (x) {
      return r.join() === x.join()
    })
  })

}

Via Active questions tagged javascript - Stack Overflow https://ift.tt/m7Z9o1i

Comments

Popular posts from this blog

ValueError: X has 10 features, but LinearRegression is expecting 1 features as input

So, I am trying to predict the model but its throwing error like it has 10 features but it expacts only 1. So I am confused can anyone help me with it? more importantly its not working for me when my friend runs it. It works perfectly fine dose anyone know the reason about it? cv = KFold(n_splits = 10) all_loss = [] for i in range(9): # 1st for loop over polynomial orders poly_order = i X_train = make_polynomial(x, poly_order) loss_at_order = [] # initiate a set to collect loss for CV for train_index, test_index in cv.split(X_train): print('TRAIN:', train_index, 'TEST:', test_index) X_train_cv, X_test_cv = X_train[train_index], X_test[test_index] t_train_cv, t_test_cv = t[train_index], t[test_index] reg.fit(X_train_cv, t_train_cv) loss_at_order.append(np.mean((t_test_cv - reg.predict(X_test_cv))**2)) # collect loss at fold all_loss.append(np.mean(loss_at_order)) # collect loss at order plt.plot(np.log(al...

Sorting large arrays of big numeric stings

I was solving bigSorting() problem from hackerrank: Consider an array of numeric strings where each string is a positive number with anywhere from to digits. Sort the array's elements in non-decreasing, or ascending order of their integer values and return the sorted array. I know it works as follows: def bigSorting(unsorted): return sorted(unsorted, key=int) But I didnt guess this approach earlier. Initially I tried below: def bigSorting(unsorted): int_unsorted = [int(i) for i in unsorted] int_sorted = sorted(int_unsorted) return [str(i) for i in int_sorted] However, for some of the test cases, it was showing time limit exceeded. Why is it so? PS: I dont know exactly what those test cases were as hacker rank does not reveal all test cases. source https://stackoverflow.com/questions/73007397/sorting-large-arrays-of-big-numeric-stings

How to load Javascript with imported modules?

I am trying to import modules from tensorflowjs, and below is my code. test.html <!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <title>Document</title </head> <body> <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@2.0.0/dist/tf.min.js"></script> <script type="module" src="./test.js"></script> </body> </html> test.js import * as tf from "./node_modules/@tensorflow/tfjs"; import {loadGraphModel} from "./node_modules/@tensorflow/tfjs-converter"; const MODEL_URL = './model.json'; const model = await loadGraphModel(MODEL_URL); const cat = document.getElementById('cat'); model.execute(tf.browser.fromPixels(cat)); Besides, I run the server using python -m http.server in my command prompt(Windows 10), and this is the error prompt in the console log of my browser: Failed to loa...