Sentiment Analysis For Google Tables Using Apps Script

2024 Update: Table’s features and capabilities are now integrated into AppSheet. Read more here.

In this post we’ll use Google Cloud’s Natural Language API to do sentiment analysis on tickets submitted to a Google Tables Support Issue Tracker.

We’ll use Google Tables as the platform for our Support Tracker and Apps Script to connect to the Cloud Natural Language API.

Here’s a GIF showing a portion of the Issue tracker to illustrate what happens when an issue ticket is submitted:

Sentiment Analysis Google Tables

The description (which someone fills out when they submit a support ticket) is sent to the Natural Language API for sentiment analysis, to determine if it’s positive (i.e. good) or negative (i.e. bad) feedback.

This information is returned to our Google Tables table and displayed as a tag alongside each row, so that we can group tickets by sentiment.

For example, we may want to prioritize tickets that are either extremely positive or extremely negative, as these are probably the most important items to double down on or fix!

Sentiment Analysis Google Tables Overview

Here’s the architecture of the system:

Google Tables Sentiment Analyzer architecture

In words:

  • User submits support ticket
  • New row of data added to our table
  • Bot is triggered and sends data to our Apps Script webhook
  • The Apps Script receives data and parses it
  • Apps Script sends data to Natural Language API
  • And receives the sentiment scores back from API
  • Apps Script parses score to create sentiment tag
  • And updates the original row of data in our table

This all happens in a under a second, so it feels almost simultaneous.

Inspiration for this idea came from the excellent sentiment analysis in Google Sheets post originally published by Alicia Williams.

Note: Since I’ve set this up using a webhook triggered by each new row, the API is called once for every new row. If we were building a high volume ticket system, we’d want to consider a different set up where we send the data through in batches and have the Apps Script running on a timer trigger instead.

Sentiment Analysis Google Tables Set Up

For this example, I’m starting with the default “New ? Support Ticket Queue” template from the Google Tables team.

1. Open Google Tables, login and select Templates > New ? Support Ticket Queue

2. Add three new columns: 1) Sentiment Score (number), 2) Sentiment Magnitude (number) and 3) Sentiment Tag (Tags).

3. Edit the new Sentiment Tag column and add the following tags: Super happy!, Happy, Satisfied, No opinion, Frustrated, Angry, Super angry!

Sentiment analysis tags in Google Tables

(You can edit these categories to whatever you want, but you’ll need them to match the tags in your Apps Script.)

Sentiment Analysis Apps Script Set Up

4. Create a blank Apps Script file in Drive or through the Apps Script dashboard

5. Clear out the boiler plate code and add the following code to declare the two global variables we need for this project (we’ll fill them in soon):

/**
 * global variables
 */
const API_KEY = ''; // <-- enter google cloud project API key
const TABLE_NAME = ''; // <-- enter google tables table ID

Since we just created our Table, let’s copy in the Table ID.

6. We find our table’s ID, by looking at the URL and copying the string right after /table/.

Table URLs can take the following form:

https://tables.area120.google.com/u/0/workspace/abcdefghijklmnop/table/TABLE_ID
https://tables.area120.google.com/u/0/table/TABLE_ID
https://tables.area120.google.com/u/0/table/TABLE_ID/view/abcedfghijk

Look for the string represented by the TABLE_ID in these fictional examples.

7. Paste this ID string into our Apps Script project, between the quotes in the line where we declare the variable TABLE_NAME:

const TABLE_NAME = ''; // <-- enter google tables table ID

Sentiment Analysis Google Cloud Set Up

This is probably the most difficult part of this whole project! 😉

For this to work, we need a Google Cloud account with billing set up. Don’t worry though, the Natural Language API is free for the first 5k “units” we use (each unit is worth 1000 characters). This is way more than we need to set this project up and test it out.

The full details of how to set up Google Cloud Natural Language API can be found in the documentation.

The steps to take are:

8. If you don’t already have a Cloud account, register for a Google Cloud account and set up billing.

9. Create a project in the Google Cloud account to use for this project.

10. Enable the Cloud Natural Language API, by clicking the link half-way down this page.

11. Create credentials for the Cloud Natural Language API. From the Cloud console choose the project we created in step 5 and navigate to APIs & Services > Credentials

Generate a new API Key through +CREATE CREDENTIALS > API key

12. Restrict the API key we generated to the Cloud Natural Language API

13. Copy the API key and paste it into our Apps Script file, between the quotes in the line where we declare the variable API_KEY (see code above):

const API_KEY = ''; // <-- enter google cloud project API key

Sentiment Analysis Google Tables Code

Staying in the Apps Script file, let’s add the webhook listener and main control function code for our program.

We use a special function called doPost(e) { } so that we can (eventually) publish our script as a web app. The doPost function sits there listening for a ping from our Google Tables bot (which we’ll set up later).

When a new row is added to our Google Table by a Form submission, the bot is triggered and sends the data we need through to our webhook.

This doPost function receives that data, parses it and sends it to the Natural Language API for sentiment analysis.

The returned sentiment data is parsed and sent back to our table to update the new row, using the patch method of the Area120Tables service.

14. Add the following doPost code:

/**
 * doPost webhook to catch data from Google Tables
 */
function doPost(e) {
  
  if (typeof e !== 'undefined') {

    // parse data
    const data = JSON.parse(e.postData.contents);

    // get the id and description
    const rowId = data.id
    const description = data.description;

    // analyze sentiment
    const sentiment = analyzeFeedback(description); // [nlScore,nlMagnitude,emotion]
    
    // combine arrays
    const sentimentArray = [rowId,description].concat(sentiment);

    // send score back to Google Tables
    const rowName = 'tables/' + TABLE_NAME + '/rows/' + rowId;
    const sentimentValues = {
      'Sentiment Score': sentiment[0],
      'Sentiment Magnitude': sentiment[1],
      'Sentiment Tag': sentiment[2]
    };
    Area120Tables.Tables.Rows.patch({values: sentimentValues}, rowName);

    return null;
  }
}

In the code above, we call a function called analyzeFeedback, so we had better declare it.

This function handles the logic around the NL scores and how to interpret them as human readable tags. Feel free to play around with the boundaries. The sentiment score is bounded between -1 (max negative) and 1 (max positive), but the magnitude only has a lower bound of 0, so can be any positive number.

For more about the interpretation of the sentiment scoring, have a read of this page in the documentation.

15. Add the following code to our Apps Script file to analyze the sentiment scores:

/**
 * Get each new row of form data and retrieve the sentiment 
 * scores from the NL API for text in the feedback column.
 */
function analyzeFeedback(description) {

  if (description !== '') {
      
      // call the NL API
      const nlData = retrieveSentiment(description);
      nlMagnitude = nlData.documentSentiment.magnitude ? nlData.documentSentiment.magnitude : 0; // set to 0 if nothing returned by api
      nlScore = nlData.documentSentiment.score ? nlData.documentSentiment.score : 0; // set to 0 if nothing returned by api
      //console.log(nlMagnitude);
      //console.log(nlScore);
    }
    else {
      
      // set to zero if the description is blank
      nlMagnitude = 0;
      nlScore = 0;

    }

    // turn sentiment numbers into tags
    let emotion = '';
    
    // happy
    if (nlScore > 0.5) { 
      
      if (nlMagnitude > 2) { emotion = 'Super happy!'; } // higher magnitude gets higher emotion tag
      else { emotion = 'Happy'; }

    }
    
    // satisfied
    else if (nlScore > 0) {  emotion = 'Satisfied'; }

    // frustrated
    else if (nlScore < 0 && nlScore >= -0.5) { emotion = 'Frustrated'; }

    // angry
    else if (nlScore < -0.5) { 
      
      if (nlMagnitude > 2) { emotion = 'Super angry!'; } // higher magnitude gets higher emotion tag
      else { emotion = 'Angry'; }
    
    }

    // if score is 0
    else { emotion = 'No opinion' }

    return [nlScore,nlMagnitude,emotion];
}

Finally we need to declare the function called retrieveSentiment to actually call the API.

16. Add the code to call the NL API:

/**
 * Calls Google Cloud Natural Language API with string from Tables
 */
function retrieveSentiment(description) {
  
  //console.log(description);

  const apiEndpoint = 'https://language.googleapis.com/v1/documents:analyzeSentiment?key=' + API_KEY;
  
  // Create our json request, w/ text, language, type & encoding
  const nlData = {
    document: {
      language: 'en-us',
      type: 'PLAIN_TEXT',
      content: description
    },
    encodingType: 'UTF8'
  };
  
  //  Package all of the options and the data together for the call
  const nlOptions = {
    method : 'post',
    contentType: 'application/json',  
    payload : JSON.stringify(nlData)
  };
  
  //  Try fetching the natural language api
  try {
    
    // return the parsed JSON data if successful
    const response = UrlFetchApp.fetch(apiEndpoint, nlOptions);
    return JSON.parse(response);
    
  } catch(e) {
    
    // log the error message and return null if not successful
    console.log("Error fetching the Natural Language API: " + e);
    return null;
  } 
}

Press save!

The full code is available here on GitHub.

Since we’re using the Area 120 Tables Apps Script service, we need to enable it for this project.

17. Go to Resources > Advanced Google services… and switch on Area120 Tables API:

Apps Script Advanced Services

Publish As Web App

18. Publish this file as a web app via the menu: Publish > Deploy as a web app…

19. Set the access to Anyone, even anonymous, as shown in this image:

Apps Script deploy as Web App

We’ll be prompted to review permissions:

Google Tables Sentiment Analyzer authorization

followed by a review of the project scopes:

Apps Script scopes

Click Allow.

This is a one-time step the first time we publish to the web or run our script (unless we add additional services in the future).

20. Copy the URL of the web app so we can paste that into our Tables bot, which we’ll create next!

Sentiment Analysis Tables Bot Set Up

The final piece of the puzzle is the bot in Google Tables.

When the issue tracker form is submitted it creates a new row of data in our table, which triggers the bot. The bot sends the data to the webhook (i.e. the code above) that handles the rest.

21. Create a new bot with the following specification:

Trigger: row added
Action: Send to webhook
Webhook URL: Our Apps Script web app URL from step 20
Webhook format: POST with JSON
Request parameters:
id : [[record_id]]
description : {{description}}

Visually, this is the bot:

Google Tables bot

The red arrow indicates where we paste the Apps Script web app URL.

Test The Sentiment Analysis Google Tables Tool

Finally, we’re ready to submit the form.

22. From the Google Table, click on the Support Ticket Form to open it in a new tab:

Google Tables Support Tracker Form

23. Submit it with a strong positive or negative sentiment in the description field (which is the one we send to the Natural Language API) to test out the Natural Language scores.

You’ll see the row of data arrive when we submit the form and then, a few moments later, the sentiment analysis columns get automatically populated too!

Sentiment Analysis Google Tables

That’s it! Let me know how you get on in the comments.

API Tutorial For Beginners With Google Sheets & Apps Script

In this API tutorial for beginners, you’ll learn how to connect to APIs using Google Apps Script, to retrieve data from a third-party and display it in your Google Sheet.

Example 1 shows you how to use Google Apps Script to connect to a simple API to retrieve some data and show it in Google Sheets:

API tutorial for beginners: Random math facts from Numbers API in Google Sheet

In Example 2, we’ll use Google Apps Script to build a music discovery application using the iTunes API:

Itunes API with Google Sheets

Finally, in example 3, I’ll leave you to have a go at building a Star Wars data explorer application, with a few hints:

Star Wars API explorer in Google Sheets using Google Apps Script

API tutorial for beginners: what is an API?

You’ve probably heard the term API before. Maybe you’ve heard how tech companies use them when they pipe data between their applications. Or how companies build complex systems from many smaller micro-services linked by APIs, rather than as single, monolithic programs nowadays.

API stands for “Application Program Interface”, and the term commonly refers to web URLs that can be used to access raw data. Basically, the API is an interface that provides raw data for the public to use (although many require some form of API authentication).

As third-party software developers, we can access an organization’s API and use their data within our own applications.

The good news is that there are plenty of simple APIs out there, which we can cut our teeth on. We’ll see three of them in this beginner api tutorial.

We can connect a Google Sheet to an API and bring data back from that API (e.g. iTunes) into our Google Sheet using Google Apps Script. It’s fun and really satisfying if you’re new to this world.

API tutorial for beginners: what is Apps Script?

In this API tutorial for beginners, we’ll use Google Apps Script to connect to external APIs.

Google Apps Script is a Javascript-based scripting language hosted and run on Google servers, that extends the functionality of Google Apps.

If you’ve never used it before, check out my post: Google Apps Script: A Beginner’s Guide

Does coding fill you with dread? In that case, you can still achieve your goals using a no-code option to sync live data into Google Sheets. Check out Coefficient’s sidebar extension that offers Google Sheets connectors for CRMs, BI tools, databases, payment platforms, and more.

Example 1: Connecting Google Sheets to the Numbers API

We’re going to start with something super simple in this beginner api tutorial, so you can focus on the data and not get lost in lines and lines of code.

Let’s write a short program that calls the Numbers API and requests a basic math fact.

Step 1: Open a new Sheet

Open a new blank Google Sheet and rename it: Numbers API Example

Step 2: Go to the Apps Script editor

Navigate to Tools > Script Editor...

Access script editor through toolbar

Step 3: Name your project

A new tab opens and this is where we’ll write our code. Name the project: Numbers API Example

Step 4: Add API example code

Remove all the code that is currently in the Code.gs file, and replace it with this:

function callNumbers() {
  
  // Call the Numbers API for random math fact
  var response = UrlFetchApp.fetch("http://numbersapi.com/random/math");
  Logger.log(response.getContentText());
  
}

We’re using the UrlFetchApp class to communicate with other applications on the internet to access resources, to fetch a URL.

Now your code window should look like this:

Numbers API Google Apps Script code

Step 5: Run your function

Run the function by clicking the play button in the toolbar:

Run Apps Script button

Step 6: Authorize your script

This will prompt you to authorize your script to connect to an external service. Click “Review Permissions” and then “Allow” to continue.

Apps Script Review Permissions

Apps Script authorization

Step 7: View the logs

Congratulations, your program has now run. It’s sent a request to a third party for some data (in this case a random math fact) and that service has responded with that data.

But wait, where is it? How do we see that data?

Well, you’ll notice line 5 of our code above was Logger.log(....) which means that we’ve recorded the response text in our log files.

So let’s check it out.

Go to menu button Execution Log

You’ll see your answer (you may of course have a different fact):

[17-02-03 08:52:41:236 PST] 1158 is the maximum number of pieces a torus can be cut into with 18 cuts.

which looks like this in the popup window:

Apps script logger output

Great! Try running it a few times, check the logs and you’ll see different facts.

Next, try changing the URL to these examples to see some different data in the response:

http://numbersapi.com/random/trivia
http://numbersapi.com/4/17/date
http://numbersapi.com/1729

You can also drop these directly into your browser if you want to play around with them. More info at the Numbers API page.

So, what if we want to print the result to our spreadsheet?

Well, that’s pretty easy.

Step 8: Add data to Sheet

Add these few lines of code (lines 7, 8 and 9) underneath your existing code:

function callNumbers() {
  
  // Call the Numbers API for random math fact
  var response = UrlFetchApp.fetch("http://numbersapi.com/random/math");
  Logger.log(response.getContentText());
  
  var fact = response.getContentText();
  var sheet = SpreadsheetApp.getActiveSheet();
  sheet.getRange(1,1).setValue([fact]);
  
}

Line 7 simply assigns the response text (our data) to a variable called fact, so we can refer to it using that name.

Line 8 gets hold of our current active sheet (Sheet1 of Numbers API Example spreadsheet) and assigns it to a variable called sheet, so that we can access it using that name.

Finally in line 9, we get cell A1 (range at 1,1) and set the value in that cell to equal the variable fact, which holds the response text.

Step 9: Run & re-authorize

Run your program again. You’ll be prompted to allow your script to view and manage your spreadsheets in Google Drive, so click Allow:

Apps Script Review Permissions

Apps script spreadsheet authorization

Step 10: See external data in your Sheet

You should now get the random fact showing up in your Google Sheet:

Random math fact from Numbers API in Google Sheet

How cool is that!

To recap our progress so far in this API Tutorial for Beginners: We’ve requested data from a third-party service on the internet. That service has replied with the data we wanted and now we’ve output that into our Google Sheet!

Step 11: Copy data into new cell

The script as it’s written in this API Tutorial for Beginners will always overwrite cell A1 with your new fact every time you run the program. If you want to create a list and keep adding new facts under existing ones, then make this minor change to line 9 of your code (shown below), to write the answer into the first blank row:

function callNumbers() {
  
  // Call the Numbers API for random math fact
  var response = UrlFetchApp.fetch("http://numbersapi.com/random/math");
  Logger.log(response.getContentText());
  
  var fact = response.getContentText();
  var sheet = SpreadsheetApp.getActiveSheet();
  sheet.getRange(sheet.getLastRow() + 1,1).setValue([fact]);
  
}

Your output now will look like this:

Random math facts from Numbers API in Google Sheet

One last thing we might want to do with this application is add a menu to our Google Sheet, so we can run the script from there rather than the script editor window. It’s nice and easy!

Step 12: Add the code for a custom menu

Add the following code in your script editor:

function onOpen() {
  var ui = SpreadsheetApp.getUi();
  ui.createMenu('Custom Numbers API Menu')
      .addItem('Display random number fact','callNumbers')
      .addToUi();
}

Your final code for the Numbers API script should now match this code on GitHub.

Step 13: Add the custom menu

Run the onOpen function, which will add the menu to the spreadsheet. We only need to do this step once.

Add custom apps script menu

Step 14: Run your script from the custom menu

Use the new menu to run your script from the Google Sheet and watch random facts pop-up in your Google Sheet!

Use custom apps script menu

Alright, ready to try something a little harder?

Let’s build ourselves a music discovery application in Google Sheets.

Example 2: Music Discovery Application using the iTunes API

This application retrieves the name of an artist from the Google Sheet, sends a request to the iTunes API to retrieve information about that artist and return it. It then displays the albums, song titles, artwork and even adds a link to sample that track:

Google Sheets and iTunes API using Apps Script

It’s actually not as difficult as it looks.

Getting started with the iTunes API Explorer

Start with a blank Google Sheet, name it “iTunes API Explorer” and open up the Google Apps Script editor.

Clear out the existing Google Apps Script code and paste in this code to start with:

function calliTunes() {
  
  // Call the iTunes API
  var response = UrlFetchApp.fetch("https://itunes.apple.com/search?term=coldplay");
  Logger.log(response.getContentText());
}

Run the program and accept the required permissions. You’ll get an output like this:

iTunes API output

Woah, there’s a lot more data being returned this time so we’re going to need to sift through it to extract the bits we want.

Parsing the iTunes data

So try this. Update your code to parse the data and pull out certain bits of information:

function calliTunes() {
  
  // Call the iTunes API
  var response = UrlFetchApp.fetch("https://itunes.apple.com/search?term=coldplay");
  
  // Parse the JSON reply
  var json = response.getContentText();
  var data = JSON.parse(json);
  
  Logger.log(data);
  Logger.log(data["results"]);
  Logger.log(data["results"][0]);
  Logger.log(data["results"][0]["artistName"]);
  Logger.log(data["results"][0]["collectionName"]);
  Logger.log(data["results"][0]["artworkUrl60"]);
  Logger.log(data["results"][0]["previewUrl"]);
  
}

Line 4: We send a request to the iTunes API to search for Coldplay data. The API responds with that data and we assign it to a variable called response, so we can use that name to refer to it.

Lines 7 and 8: We get the context text out of the response data and then parse the JSON string response to get the native object representation. This allows us to extract out different bits of the data.

So, looking first at the data object (line 10):

iTunes api data packet

You can see it’s an object with the curly brace at the start {

The structure is like this:

{
resultCount = 50,
results = [ ....the data we're after... ]
}

iTunes api data packet

Line 11: we extract the “results”, which is the piece of data that contains the artist and song information, using:

data["results"]

Line 12: There are multiple albums returned for this artist, so we grab the first one using the [0] reference since the index starts from 0:

data["results"][0]

This shows all of the information available from the iTunes API for this particular artist and album:

iTunes api data results

Lines 13 – 16: Within this piece of data, we can extract specific details we want by referring to their names:

e.g. data["results"][0]["collectionName"]

to give the following output:

iTunes api details

Use comments (“//” at the start of a line) to stop the Logger from logging the full data objects if you want. i.e. change lines 10, 11 and 12 to be:

// Logger.log(data);
// Logger.log(data[“results”]);
// Logger.log(data[“results”][0]);

This will make it easier to see the details you’re extracting.

Putting this altogether in an application

If we want to build the application that’s showing in the GIF at the top of this post, then there are a few steps we need to go through:

  • Setup the Google Sheet
  • Retrieve the artist name from the Google Sheet with Google Apps Script
  • Request data from iTunes for this artist with Google Apps Script
  • Parse the response to extract the relevant data object with Google Apps Script
  • Extract the specific details we want (album name, song title, album artwork, preview url)
  • Clear out any previous results in the Google Sheet before showing the new results
  • Display the new results in our Google Sheet
  • Add a custom menu to run the program from the Google Sheet, not the script editor

It’s always a good idea to write out a plan like this before you commit to writing any lines of code.

That way you can think through the whole application and what it’s going to do, which allows you to make efficient choices with how you setup your code.

So the first thing to do is setup a Google Sheet. I’ll leave this up to you, but here’s a screenshot of my basic Google Sheet setup:

iTunes Google Sheet

The important thing to note is the location of the cell where a user types in the artist name (11th row, 2nd column) as we’ll be referring to that in our code.

iTunes API Explorer code

And here’s the Google Apps Script code for our application:

// --------------------------------------------------------------------------------------------------
//
// iTunes Music Discovery Application in Google Sheets
//
// --------------------------------------------------------------------------------------------------

// custom menu
function onOpen() {
  var ui = SpreadsheetApp.getUi();
  ui.createMenu('Custom iTunes Menu')
      .addItem('Get Artist Data','displayArtistData')
      .addToUi();
}

// function to call iTunes API
function calliTunesAPI(artist) {
  
  // Call the iTunes API
  var response = UrlFetchApp.fetch("https://itunes.apple.com/search?term=" + artist + "&amp;limit=200");
  
  // Parse the JSON reply
  var json = response.getContentText();
  return JSON.parse(json);
  
}


function displayArtistData() {
  
  // pick up the search term from the Google Sheet
  var ss = SpreadsheetApp.getActiveSpreadsheet();
  var sheet = ss.getActiveSheet();
  
  var artist = sheet.getRange(11,2).getValue();
  
  var tracks = calliTunesAPI(artist);
  
  var results = tracks["results"];
  
  var output = []
  
  results.forEach(function(elem,i) {
    var image = '=image("' + elem["artworkUrl60"] + '",4,60,60)';
    var hyperlink = '=hyperlink("' + elem["previewUrl"] + '","Listen to preview")';
    output.push([elem["artistName"],elem["collectionName"],elem["trackName"],image,hyperlink]);
    sheet.setRowHeight(i+15,65);
  });
  
  // sort by album
  var sortedOutput = output.sort( function(a,b) {
    
    var albumA = (a[1]) ? a[1] : 'Not known';  // in case album name undefined 
    var albumB = (b[1]) ? b[1] : 'Not known';  // in case album name undefined
    
    if (albumA &lt; albumB) { return -1; } else if (albumA &gt; albumB) {
      return 1;
    }
    // names are equal
    return 0;
  });
  
  // adds an index number to the array
  sortedOutput.forEach(function(elem,i) {
    elem.unshift(i + 1);
  });
  
  var len = sortedOutput.length;
  
  // clear any previous content
  sheet.getRange(15,1,500,6).clearContent();
  
  // paste in the values
  sheet.getRange(15,1,len,6).setValues(sortedOutput);
  
  // formatting
  sheet.getRange(15,1,500,6).setVerticalAlignment("middle");
  sheet.getRange(15,5,500,1).setHorizontalAlignment("center");
  sheet.getRange(15,2,len,3).setWrap(true);
  
}

Here’s the iTunes API script file on GitHub.

How it works:

Let’s talk about a few of the key lines of code in this program:

Lines 16 – 25 describe a function that takes an artist name, calls the API with this artist name and then returns the search results from the API. I’ve encapsulated this as a separate function so I can potentially re-use it elsewhere in my program.

The main program starts on line 28.

On line 34, I retrieve the name of the artist that has been entered on the Google Sheet, and we call our API function with this name on line 36.

On lines 42 – 47, I take the results returned by the API, loop over them and pull out just the details I want (artist name, album name, song title, album artwork and preview track). I push all of this into a new array called output.

Next I sort and add an index to the array, although both of these are not mandatory steps.

On line 68, I clear out any previous content in my sheet.

Then on line 71, I paste in the new data, starting at row 15.

Finally, lines 74 – 76 format the newly pasted data, so that the images have space to show properly.

Run the onOpen() function from the script editor once to add the custom menu to your Google Sheet. Then you’ll be able to run your iTunes code from the Google Sheet:

Custom iTunes API menu

Now you can run the program to search for your favorite artist!

More details on the iTunes API:

Documentation for searching the iTunes Store.

Documentation showing the search results JSON packet.

Example 3: Star Wars data explorer using the Star Wars API

This one is a lot of fun! Definitely the most fun example in this API Tutorial for Beginners.

The Star Wars API is a database of all the films, people, planets, starships, species and vehicles in the Star Wars films. It’s super easy to query and the returned data is very friendly.

Star Wars API in Google Sheet

It’s a little easier than the iTunes API because the data returned is smaller and more manageable, and therefore easier to parse when you first get hold of it.

Getting started with the Star Wars API

As with both the previous APIs, start with a simple call to see what the API returns:

/*
 * Step 1:
 * Most basic call to the API 
 */
function swapi() {
  
  // Call the Star Wars API
  var response = UrlFetchApp.fetch("http://swapi.dev/api/planets/1/");
  Logger.log(response.getContentText());
}

The data returned looks like this:

API Tutorial for Beginners: Star Wars API data

So, it’s relatively easy to get the different pieces of data you want, with code like this:

/*
 * Step 2:
 * Same basic call to the API 
 * Parse the JSON reply
 */
function swapi() {
  
  // Call the Star Wars API
  var response = UrlFetchApp.fetch("http://swapi.dev/api/planets/1/");
  
  // Parse the JSON reply
  var json = response.getContentText();
  var data = JSON.parse(json);
  Logger.log(data);
  Logger.log(data.name);
  Logger.log(data.population);
  Logger.log(data.terrain);
}

Well, that should be enough of a hint for you to give this one a go!

Some other tips

In addition to custom menus to run scripts from your Google Sheet, you can add Google Sheets buttons and connect them to a script to run the script when they are clicked. That’s what I’ve done in this example.

On the menu, Insert > Drawing...

Google Sheets insert drawing

Create a button using the rectangle tool:

Google Sheet drawing tool

Finally, right click the drawing when it’s showing in your sheet, and choose Assign Script and type in the name of the function you want to run:

Google Sheet drawing assign script

What else?

Use this CHAR formula to add stars to your Google Sheet:

=CHAR(9734)

I used the font “Orbitron” across the whole worksheet and, whilst it’s not a Star Wars font, it still has that space-feel to it.

The big Star Wars logo is simply created by merging a bunch of cells and using the IMAGE() formula with a suitable image from the web.

Finally, here’s my SWAPI script on GitHub if you want to use it.

API Tutorial for Beginners: Other APIs to try

Here are a few other beginner-friendly APIs to experiment with:

> Giphy API. Example search endpoint: Funny cat GIFs

> Pokémon API. Example search endpoint: Pokemon no. 1

> Open Movie Database API. Example search endpoint: Batman movies

> International Space Station Current Location. Example search endpoint: ISS current location

Also, here’s the official Google documentation on connecting to external APIs.

Finally, here’s a syntax guide for the common forms of API Authentication using Apps Script.

Let me know in the comments what you do with all these different APIs!

Disclosure: Some of the links in this post are affiliate links, meaning I’ll get a small commission if you click the link and subsequently signup to use that vendor’s service. I only do this for tools I use myself and wholeheartedly recommend.

Community Connectors: Access all your data in Google Data Studio

Data Studio is relatively new dashboard tool from Google, launched in mid-2016. It’s a superb tool for creating professional looking reports, easily and quickly, and it connects seamlessly to other Google data sources (e.g. Analytics, AdSense, Sheets, …).

Here’s an introduction to Data Studio and a look at the more advanced features.

GitHub commit dashboard, built with the new native data Community Connector
GitHub commits dashboard, built in Data Studio using a native Data Connector

Do you work with data outside of Google’s ecosystem though?

I’ll go out on a limb here, and say, yes, most likely you do.

Perhaps you’re a digital marketing analyst looking at Facebook, Twitter, Instagram, MailChimp data (etc…) for example.

Many of us work with other web services and you want that data displayed in Data Studio. With the launch of native data Community Connectors, you can connect to your favorite web services and access data that lives outside the Google ecosystem directly!

What is a Data Studio Community Connector?

Data Studio Community Connector example
Data Studio Community Connector example with the MailChimp API (click to enlarge)

Continue reading Community Connectors: Access all your data in Google Data Studio

Show data from the GitHub API in Google Sheets, using Apps Script and Oauth

This post shows you how to connect a Google Sheet to GitHub’s API, with Oauth and Apps Script. The goal is to retrieve data and information from GitHub and show it in your Google Sheet, for further analysis and visualization.

If you manage a development team or you’re a technical project manager, then this could be a really useful way of analyzing and visualizing your team’s or project’s coding statistics against goals, such as number of commits, languages, people involved etc. over time.

Contents

  1. What are Git and GitHub?
  2. Access GitHub API using Basic Authentication
  3. Access GitHub API using OAuth2 Authentication
  4. Resources and further reading

Note, this is not a post about integrating your Apps Script environment with GitHub to push/pull your code to GitHub. That’s an entirely different process, covered in detail here by Google Developer Expert Martin Hawksey.

Continue reading Show data from the GitHub API in Google Sheets, using Apps Script and Oauth

Google Sheets and Mailchimp integration using Apps Script

In this post, we’re going to see how to setup a Google Sheets and Mailchimp integration, using Apps Script to access the Mailchimp API.

The end goal is to import campaign and list data into Google Sheets so we can analyze our Mailchimp data and create visualizations, like this one:

Google Sheets and Mailchimp integration for campaign data analysis

Mailchimp is a popular email service provider for small businesses. Google Sheets is popular with small businesses, digital marketers and other online folks. So let’s connect the two to build a Mailchimp data analysis tool in Google Sheets!

Once you have the data from Mailchimp in a Google Sheet, you can do all sorts of customized reporting, thereby saving you time in the long run.

I use Mailchimp myself to manage my own email list and send out campaigns, such as this beginner API guide (Interested?), so I was keen to create this Mailchimp integration so I can include Mailchimp KPI’s and visualizations in my business dashboards.

For this tutorial I collaborated with another data-obsessed marketer, Julian from Measure School, to create a video lesson. High quality video tutorials are hard to create but thankfully Julian is a master, so I hope you enjoy this one:

(Be sure to check out Julian’s YouTube channel for lots more data-driven marketing videos.)

If you’re new to APIs, you may want to check out my starter guide, and if you’re completely new to Apps Script, start here.

Otherwise let’s begin.
Continue reading Google Sheets and Mailchimp integration using Apps Script