All you need to do is add your data to a spreadsheet, then create your own Autocrat template document in Google Docs, with > that reference columns in your spreadsheet. You'll need to manually refresh it when you want new data, but that's perfect if you want to compare data over time and already do that in a spreadsheet on a regular basis.īest for: Turning your data into template documentsĪutocrat allows you to turn your data into beautiful documents. Google Analyticsįor a simpler way to see just the data you need-and turn it into reports-the Google Analytics Sheets add-on can pull in any analytics data you want and save it to spreadsheet tables. Use this tool to track customer sentiment by adding queries and keywords associated with your brand, or save tweets from conferences and webinars. Tweets are pulled every hour, and matching tweets are automatically pulled into your sheet. With the add-on, you can save tweets for any search query, keyword, or hashtag and the results will populate into a Google Sheet. Tweet Archiver allows you to glean insights from Twitter without actually having to open the app. Tweet Archiverīest for: Saving tweets for any search keyword or hashtag Just search for what you're looking for, click the result that looks closest, and Knoema will insert a table of the data into your spreadsheet. Need detailed statistics on population, crime statistics, exports, land use, and other academic topics? Knoema Data Finder gives you a sidebar to search through and import data on these and dozens of other topics from governments and industry sources around the globe. Related: Want to import info from RSS feeds? Check out RSS by Zapier. The tool also offers a variety of pre-made templates to help you streamline your reporting process. Supermetrics will then pull in your data and can refresh it on a schedule to keep your spreadsheet up to date. To import data, select the connection and query type, add filters to only watch for specific data, and then choose the fields you want added to your spreadsheet. It connects to analytics tools like Google Analytics and Moz, social networks including Facebook, Twitter, and YouTube, payment services like Stripe, along with ads services, databases, and more. Supermetrics is a powerful tool to import your business data into Google Sheets. Supermetricsīest for: Pulling and blending data from 90+ marketing and sales tools You can also do this using Schedule by Zapier with Google Sheets and the other apps you rely on for your business-critical workflows. You can choose how often you'd like to pull data from external tools, with options including hourly, daily, monthly, or on specific days of the week. If you work on reports at a regular interval, Coupler.io can be a helpful tool that automatically exports data from popular software like QuickBooks, Shopify, and HubSpot into Google Sheets on a set schedule. Python to JSON: Type ConversionĪ process of type conversion occurs as well when we convert a dictionary into a JSON string.Best for: Exporting data from various apps on a set schedule So the return value of this function was definitely a string. If we check the data type of this variable, we see: This helps us confirm that, indeed, the original dictionary is now represented as a string with JSON format. In the Python dictionary, this value was False but in JSON, the equivalent value is false. □ Tip: Notice that the last value ( false) was changed. Now that you know what the JSON format is used for, let's see its basic structure with an example that represents the data of a pizza order: For example, to create a Google Chrome App, you need to include a JSON file called manifest.json to specify the name of the app, its description, current version, and other properties and settings. ![]() ![]() Configuration files: JSON is also used to store configurations and settings.Web Development: JSON is commonly used to send data from the server to the client and vice versa in web applications.Its common use cases include web development and configuration files. JSON is basically a format used to store or represent data. But since then it has become a language-independent data format and most of the programming languages that we use today can generate and read JSON. The JSON format was originally inspired by the syntax of JavaScript (a programming language used for web development). How to write to JSON files in Python using dump()Īre you ready? Let's begin! ✨ □ Introduction: What is JSON?.How to read JSON files in Python using load().How to indent JSON strings automatically.How to convert JSON strings to Python objects and vice versa.How to work with the Python built-in json module.How JSON and Python Dictionaries work together in Python.Welcome! If you want to learn how to work with JSON files in Python, then this article is for you.
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