IMPORTDATA lets you fetch data from published online CSV files. It’s a good solution, but not the best one. Why? It lacks advanced features that can improve user experience and productivity. We claim that Coupler.io can do better than IMPORTDATA, and this article is meant to prove that. So, let’s try out both solutions in real-life use cases to come to an unbiased verdict.

What is IMPORTDATA and how does it work?

IMPORTDATA is a Google Sheets function that imports data from a given URL in either CSV (comma-separated value) or TSV (tab-separated value) format.

IMPORTDATA syntax

• IMPORTDATA(“URL”)
  • URL is the location of a .csv or .tsv file containing the data to be imported. The URL must be specified, including the protocol.
  • Example:

=IMPORTDATA("https://www.quandl.com/api/v3/datasets/EUREX/FCPEG2020.csv?api_key=eVEFx_xdJBXEHGnmu3sc")

• IMPORTDATA(reference-to-cell)
  • reference-to-cell is a reference to a cell within Google Sheets, which contains the URL. 
  • Example:

=IMPORTDATA(C3)

IMPORTDATA formula examples

Case #1: Direct reference to the URL

=IMPORTDATA("https://www.quandl.com/api/v3/datasets/EUREX/FCPEG2020.csv?api_key=eVEFx_xdJBXEHGnmu3sc")

• 

Case #2: Reference to the cell containing the URL

=IMPORTDATA(Sheet2!C3)

• 

IMPORTDATA pros and cons

Pros	Cons
Fast and simple implementation No installation required You can import data from online published CSV, TSV, and TXT files You can adjust the number of rows and columns to be imported	Maximum of 50 IMPORTDATA calls on a single spreadsheet You are not secured from data loss as each error cleans your data Only manual re-import is available The date values need to be manually updated to the date format

What is Coupler.io?

Coupler.io is a Google Sheets add-on that lets you connect different data sources with spreadsheets. To import data from published online CSV files, you need to install the add-on and set up a CSV importer. We blogged about this in detail in “Import CSV into Google Sheets Without Any Coding”. Here is how the CSV importer at Coupler.io works:

• 

Coupler.io CSV importer pros and cons

Pros

Cons

Provides security from total data loss if any error occurs Lets you use headers parameter to provide authentication credentials for data import from secured sources Data re-import automation on a schedule Lets you select the number of rows and columns, as well as the order of columns to be imported Lets you set up the target cell to get output where you need it Lets you place data imported from multiple sources (with the same fields structure and order) Lets you make more precise data import requests The date values are automatically converted into the date format

Requires installing the add-on and setting up the CSV importer

IMPORTDATA vs. Coupler.io

TL;DR comparison table

IMPORTDATA	Feature	Coupler.io
Each error cleans your data	Error dependency	You are always safe from data loss if any error occurs
Maximum of 50 calls on a single spreadsheet	Limitations	Google Spreadsheets limits or Google Sheets API limits
No support has been officially claimed	Import from CSV links with authentication	Available
Not supported	Data update on schedule	Available
Available with the help of the QUERY function	Data import with a selected number of columns	Available
Not supported	Columns reordering	Available
Available with the help of the QUERY function	Data import with a limited number of rows	Available
Available with the help of the QUERY function	Advanced requests	Available
Not supported	Import data from secured URLs	Available
Not supported	Append imported data	Available
Manual	Date format recognition	Automatic

Now, let’s check out how good both IMPORTDATA and Coupler.io are in real-life use cases. For this, we’ll inspect additional features available with each solution and demonstrate the outcome. Let the battle begin! 

Data update on demand

After the initial import, you may want to update the data fetched from your online CSV file. With IMPORTDATA, you’ll have to manually execute the function. With Coupler.io, you need to click on the Run Importer button to update the data on demand. 

Data update on schedule

Coupler.io provides the automatic data refresh feature. Select the frequency for data re-syncs and the data will be automatically imported on a set schedule. IMPORTDATA lacks any scheduling option.

Import data with a selected number of columns

You can select the number of columns to be imported via IMPORTDATA. For this, you’ll need to apply a combination of two functions: IMPORTDATA and QUERY. For example, here is how you can select columns #1,#2, and #3:

=QUERY(IMPORTDATA("https://www.quandl.com/api/v3/datasets/EUREX/FCPEG2020.csv?api_key=eVEFx_xdJBXEHGnmu3sc"),
 "Select Col1,Col2,Col3")

• 

Read our blog post about QUERY Google Sheets function to learn more data manipulation capabilities.

With Coupler.io, you can also cut off the unnecessary columns. For this, there is the Fields parameter, where you need to type relevant column names separated by comma. An extra benefit is that the order of names you specify will result in the order of columns for output. An important note is that you have to be sure such headers are first row in the output result. For example, let’s import the columns that we fetched using QUERY+IMPORTDATA, but in a reversed order (High, Open and Date):

• 

Import data with a limited number of rows

Both solutions also allow you to limit the total number of rows to be imported. For IMPORTDATA, you’ll need the QUERY function again. For example, here is how to limit your output to 10 rows:

=QUERY(IMPORTDATA("https://www.quandl.com/api/v3/datasets/EUREX/FCPEG2020.csv?api_key=eVEFx_xdJBXEHGnmu3sc"),
 "Select * limit 10")

• 

In Coupler.io, you can cut off the unnecessary rows using the URL query string parameter. Let’s limit our output to 10 rows again:

• 

You can also skip rows from the top of the CSV file. This is useful when you want to cut off notation data before table structured data or column headers. For this, you need to specify the number of rows to be skipped in the Skip rows field of the CSV importer. For example, let’s skip 2 rows:

• 

Import data with conditions

Again, a combination of QUERY and IMPORTDATA broadens your importing capabilities. You can set up conditions for fetching data. For example, let’s import values in the Settle column that exceed 115: 

=QUERY(IMPORTDATA("https://www.quandl.com/api/v3/datasets/EUREX/FCPEG2020.csv?api_key=eVEFx_xdJBXEHGnmu3sc"),
 "Select * where Col5 > 115",1)

• 

With Coupler.io, you can use the URL query string parameter to make more precise requests, such as time ranges, users, and so on. This feature is usually available if you pull data from secured connections for API-styled requests. So, the parameters available will differ. For example, we use a CSV dataset stored on Quandl. Their API provides certain times-series parameters to customize dataset prior to download. Here is how you can fetch data rows on and after the specified start date: 2020-01-07. 

• 

Import data from secured CSV URLs

In the examples above, we fetched data from a publicly available CSV file, which did not require any authentication. It contained an API key attached to the URL (csv?api_key=eVEFx_xdJBXEHGnmu3sc), so IMPORTDATA had no issues with pulling data from there. However, the function won’t work the same as with secured URLs. For example, let’s try to import a Clockify report from a CSV file:

https://global.api.clockify.me/workspaces/5e450bcf1fdfac54e1b1e0e3/reports/summary?export=csv

• 

With Coupler.io, you can cope with this task using such parameters as Request headers, Request body and HTTP method. Parameters will always differ depending on the app you’re fetching data from. Check out our blog posts Connect Jira Server to Google Sheets and Connect Clockify to Google Sheets for details. Here is how it works on the example of the Clockify link:

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Append imported data

If you want to place data from multiple sources that have the same structure and order of columns, check out the APPEND mode in the Settings. You can set up a few importers and fetch data from all the CSV files without any distortion. This is quite useful for cases when you need to combine monthly reports into a single year report. Check out how it works: 

• 

If you want to do the same using the IMPORTDATA function, you’ll have to manually place formulas to cells and apply the QUERY function to skip the first row. 

Date format recognition

An attentive reader will have noticed that the data fetched with IMPORTDATA and Coupler.io differ a bit:

• 

Google Sheets does not recognize date values and, hence, you’ll have to update their format manually after the import. With Coupler.io, you won’t need to spend your time on this. 

To wrap up: which solution should I choose for my needs?

If you import data from online published CSV docs from time to time, IMPORTDATA is likely a good fit. It’s simple to use and does not require any prerequisites. Moreover, you can enhance its import capabilities if you combine it with the QUERY function. Coupler.io with its CSV importer is the best option for recurrent import. You can automate data fetching and benefit from lots of available features. Besides, the Coupler.io team is working on different ready-to-use integrations, such as Jira Cloud, Xero, and others. Check them out on our blog. Feel free to provide your feedback in the comments section, and good luck with your data!

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