How to Parse Data in Google Sheets

In many businesses, Google Sheets is likely the go-to for a lot of data needs. Whether it’s customer data sales information, or analytical numbers, there’s probably a lot of critical info already stored there. So, when it comes to adding new forms of data, such as from web scraping, can you still use it?

Sure! It’s not perfect, but for many needs, you can. The challenge lies in parsing the data in Google Sheets itself. In other words, it’s important to know how to take raw data and turn it into something Google Sheets can use or work with.

Which, as you might have guessed from the title, is exactly what we’re going to talk about 😉

Looking For Proxies?

Residential, datacenter, mobile… we’ve got everything you need!

Take A Look

Once you learn how to parse data in Google Sheets, you can use it to help with a variety of business decisions, research, and management of critical data for your company. Without a doubt, there are a few steps to overcome in this process, and depending on the skill and experience you have, you will need to choose one or more methods to use. To help you parse data in Google Sheets, we’ve broken down the process for you here so you can get started.

What Does a Google Sheets Parser Do?

Let’s start at the beginning. What is parsing? Parsing is the process of taking raw data and extracting valuable bits and pieces from it that fit the specific parameters you have set. There are numerous ways to do so and many, many reasons why this is a critical step. Understanding data parsing will enable you, as a business owner, to truly use all of the data you have to make better decisions and, in some situations, to influence the way you operate your company. 

Consider what you may want to parse data for that is tucked into your Google Sheets. For example, some companies may want to parse data into Google Sheets. That means you can parse the data you have from other resources and put it into Google Sheets to use. Alternatively, and more often, it is necessary to use the data in Google Sheets to make those critical decisions. You can use it to inform your bigger business intelligence decisions. (One way to do this is through Looker Studio – something we will get into in just a bit.) 

Why would you do this? Think about a few of the ways parsing data in Google Sheets could be helpful to you and your business.

• You are a real estate agent. You need very specific details about a property or a group of properties recently sold. Extract real estate listings and parse that data to find exactly what you need.
• You are working on a project with web data integration that requires very specific steps. You can extract web data integration information and use it to help influence the decisions you make, ensuring accuracy and reducing mistakes. 
• Your business stores all of your data in Google Sheets. It’s where you know what you sold and who your customers are. You can use a Google Sheets parser to track down specific data statistics and create better insights for your company.
• Capture datasets with accuracy. You know the importance of data in business decisions. When you parse data in Google Sheets, you can use that information for a wide range of tasks.

Let’s be specific here. Parsing data in Google Sheets makes that data more usable to you, no matter the project. The end result is you can use that data to make better decisions, save money, product better service, or otherwise enhance your profit margins. 

How to Parse Data in Google Sheets

Now that you know the value of the process, consider how you can parse data in Google Sheets with a simple function and when to get started. To parse data in Google Sheets, you will need to access it, extract the structured information stored in online spreadsheets, analyze it, and then use that data. You can do this manually, or you can use a Google Sheets parser to automate the process.

Parsing data in Google Sheets can be done using various tools. The following are some of the most effective methods to do so.

Google Sheets API: The simplest method that works for those who need to parse data that Google Sheets maintains is to use the Google Sheets API. This platform is built on JSON and HTTP. You are able to use it to parse data from the Google Sheets you are using programmatically. Note that you can also use this method to parse data to Google Sheets as well.

To do so, you will need to enable the Google Sheets API within your Google Cloud Project. Luckily, Google offers a streamlined guide that can help you get over some of the more challenging aspects of this process. You will need to go through a brief authentication process to gain access. 

You will then be able to use client libraries to support the process, including libraries designed for Python, Java, Go, and Node.js. This can make the requests to the API a bit more effective. It also makes parsing responses more effortless. Consider these strategies that may help with the process:

• If you are reading data, you can use spreadsheets.values.get to read cell values, ranges, or the entire sheet itself. 
• If you are parsing JSON, you can count on the API to return data in JSON format. You can then parse that data using JSON parsers that are available for the language you have selected. 
• Use the ValueInputOption to control how the data values are parsed. For example, USER_ENTERED or RAW.
• You can use methods such as spreadsheets.values.update for a specific range in the sheet.
• For specific cells, use the A1 notation. 

You can parse data in Google Sheets quickly using these steps. There is a bit of a learning curve, and that could play a role in the processes you select.

Another option is to use libraries like gspread for Python. Gspread is built on the Google Sheets API. It was created as a wrapper with the purpose of ensuring that Google Sheets could be easily accessible. It enables the operations that need to be performed on the go and incorporates helper functions.

If you want to parse data in Google Sheets using Python, gspread is the route to take to make it happen. With it, you can:

• Easily connect to a Google Sheet
• Work through the authentication process to gain access
• Retrieve and update data programmatically 

This process allows you to read the entire sheet, if you would like to do so. Or, which is more common, you may want to source data that is from a specific range of details, which is also something you can do. You can also filter that data based on the custom logic that is applicable to your business.

Parsing Data in Google Sheets: Strategies and Tips

Parsing Google Sheets often includes managing authentication with OAuth, handling different data types (like dates, numbers, and strings), and cleaning the extracted data for consistency. This approach is widely used for building dashboards, automating workflows, or integrating live spreadsheet data into websites and apps.

Let’s breakdown some of the components of that process so you can start to parse data in Google Sheets.

Using the SPLIT function: The SPLIT function is one way to parse data in Google Sheets, as it allows you to cut a cell’s content into more than one part based on the delimiter. 

Here is what this may look like:

=SPLIT(text, delimiter, [split_by_each], [remove_empty_text])

The text here is the information you want to split, while the delimiter should be the character that defines where to split the text. The split by each field, if true, splits the character in the delimiter, while the remove empty text, if true, removes empty text pieces. 

Parsing times and dates: Another important step you will likely need to master as you parse data in Google Sheets is parsing dates and times, which is harder than you may have thought. That’s because dates are often in a text string, which means it becomes necessary to extract them. The REGEXEXTRACT function allows you to do this. 

=SPLIT(text, delimiter, [split_by_each], [remove_empty_text])

You will use the date format YYYY-MM-DD to do so.

Looking For Proxies?

Residential, datacenter, mobile… we’ve got everything you need!

Take A Look

TEXT Function: This is another tool that will be necessary to learn if you need to parse data by converting it into a more beneficial format for your use. The TEXT function allows you to do this by changing how the data shows up. If you want, for example, to change the format of a column of dates, you could use:

=TEXT(A1, "mmmm dd, yyyy")

In doing so, it turns the dates into that desired format.

Columns Features: The text to columns feature is another helpful component. It is very common for data to be presented in a large block of text (if you use CSV files, you already know that). To pull data from that information, then, you need to use the Text to Columns feature. This is a feature in Google Sheets that will parse the data down easily. It will split the cell’s content into separate columns based on what you provide in the delimiter. 

To use the Text to Columns feature, highlight the column you want to split. Then, go to Data – Split text to columns. This gives you the option to select the delimiter you need. The tool then does the entire process for you.

Cleaning Data: As you consider these tips to parse Google Sheets effectively, know that there are times when you need to clean up the data. Cleaning it up removes excessive information and gets rid of many of the problems that stem from real-world data. To do this, we use the TRIM and CLEAN functions.

As you parse data in Google Sheets, know the following:

• TRIM will remove extra spaces from the data you are parsing. 
• CLEAN takes out non-printable characters from the data you are parsing. 

It is quite common to need to use this process. And, it’s easy to do. Just wrap the data in the following functions:

The formula isn’t hard to do, but it will produce the desired results. You can then analyze that data in whatever method fits your goals and objectives.

Third Party Sources: As noted, there are some situations where you may want to use a Google Sheets parser to help you with data from external sources. As noted, you can use the Looker Studio feature that we linked to previously. 

=TRIM(CLEAN(A1))

Alternatively, if the content you need to parse is outside of Google Sheets, the IMPORT functions can help. These include IMPORTHTML, IMPORTXML, and IMPORTRANGE.

If, for example, you want to important data that is in a table on a website into your Google Sheet, you can use the IMPORTHTML method using the following:

=IMPORTHTML("https://example.com", "table", 1)

You will then be able to manipulate that information as you see fit to put it into your Google sheet.

When you take these steps to navigate the process to parse data, Google Sheets information becomes more accessible and useful for you. This process is very commonly necessary for a variety of tasks, as mentioned, including automating workflows or integrating live spreadsheet data into your app or a website. It helps to make that information more accessible and useful for the way you need to use it. Google Sheets is such a commonly used data tool that you should know how to manage it and how to parse data in Google Sheets with ease.

How Rayobyte Can Help You With Google Sheets Parser

When it comes time to parse data Google Sheets steps listed above will make that possible. Let Rayobyte help you with the process. You can parse Google Sheets with data that you scrape from the Rayobyte API, for example, allowing you to easily manipulate information. Parsing data in Google Sheets using our proxy service can also be helpful. Learn more by contacting Rayobyte today.

The information contained within this article, including information posted by official staff, guest-submitted material, message board postings, or other third-party material is presented solely for the purposes of education and furtherance of the knowledge of the reader. All trademarks used in this publication are hereby acknowledged as the property of their respective owners.