Why use the Qualtrics API to mange survey data analysis?
An API, or Application Programming Interface, is a set of rules and protocols that defines how different software systems can communicate with each other. APIs are commonly used to allow third-party developers to access and use the data and functionality of a software system or platform. For example, the Qualtrics API allows researchers to write programs that can automate data analysis of surveys collected by the Qualtrics platform.
Using the Qualtrics API to automate survey data analysis can have several benefits, including:
- Speed: Automating survey cleaning can save you time by allowing you to quickly and easily process large amounts of survey data without having to manually clean and prepare the data.
- Accuracy: Automating survey cleaning can also improve the accuracy of your data by ensuring that data is consistently cleaned and processed using the same rules and procedures.
- Consistency: Automating survey cleaning can help you ensure that your data is consistent and free of errors, which can improve the reliability and validity of your analysis.
- Flexibility: The Qualtrics API allows you to customise the survey cleaning process to fit your specific needs, so you can tailor the process to your unique requirements.
- Ease of use: The Qualtrics API is easy to use and offers a range of tools and functions for automating survey cleaning, making it an efficient and effective way to process survey data.
How to get started
To use the Qualtrics API, you will need to have a Qualtrics account and obtain an API token. You can do this by going to the “API & Integrations” section of your account settings and clicking the “Generate Token” button.
The Qualtrics API can be used with a variety of programming languages to automate survey cleaning. Two of the most common are R and Python.
Accessing your Qualtrics data with R
You can use the QualtricsR package to access and retrieve data from surveys created on the Qualtrics platform using the R programming language. To get started, you’ll need to have an account with Qualtrics and install the QualtricsR package in R. You can install the package by running the following command in the R console:
install.packages("QualtricsR")
Once the package is installed, you can load it into your R session with the library function:
library(QualtricsR)
The qualtrics_api_credentials() function is used to set the API credentials that are required to authenticate your API requests.
You can find your API Key and Data Center ID in your Qualtrics account settings. Here’s an example of how you can use the qualtrics_api_credentials() function to set your API credentials:
qualtrics_api_credentials(api_key = "XXXXX", #replace with your API
base_url = "XXX.XXX1.qualtrics.com", #replace with your data center
install = FALSE, #optional: save credentials to your R environment
overwrite = FALSE #optional: overwrites any previously saved Qualtrics API credentials
)
#If you choose to store your credentials, you can retrieve them in later sessions with:
readRenviron("~/.Renviron")
With the connection established, you can use the various functions in the QualtricsR package to retrieve data from your surveys. For example, you can use the all_surveys function to retrieve and print a list of all the surveys in your account:
surveys <- all_surveys()
print(surveys)
You can then use the GetSurvey function to retrieve the data for a specific survey:
# Retrieves the second survey on the survey list printed in the previous step
mysurvey <- fetch_survey(
surveyID = surveys$id[2], #edit this to match survey of interest,
#save_dir = "data/", #use this if you want to save the data to your drive.
label = FALSE, #if true, returns data as labels instead of raw values
force_request = TRUE, #default behaviour is to fetch a cached version of the survey if available - set this to TRUE to get the latest survey from Qualtrics each time
)
Accessing your Qualtrics data with Python
For Python, once you have the API key setup, you can use the requests library in Python to make API requests to the Qualtrics API. First, install the requests library if you don’t already have it:
pip install requests
Next, import the requests library and use it to make an API request to the Qualtrics API. For example, you can use the following code to retrieve a list of all the surveys in your account:
api_key = "YOURAPIKEY"
base_url = "https://YOURDATACENTERID.qualtrics.com/API/v3/"
url = f"{base_url}/surveys"
headers = {
"Content-Type": "application/json",
"X-API-TOKEN": api_key
}
response = requests.get(url, headers=headers)
if response.status_code == 200:
surveys = response.json()
print(surveys)
else:
print(f"Error getting survey list: {response.status_code}")
This code sends a GET request to the /surveys endpoint of the Qualtrics API, which returns a list of all the surveys in your account. The response is returned as a JSON object, which you can access and manipulate in Python.
To retrieve the data for a specific survey, you can use the /surveys/{surveyId}/export-responses/ endpoint of the API, passing in the surveyId of the survey you want to retrieve data for. For example:
survey_id = "your_survey_id_here"
url = f"{base_url}/surveys/{survey_id}/export-responses"
payload = {"format": "csv"}
response = requests.request("POST", url, json=payload, headers=headers)
if response.status_code == 200:
survey_data = response.json()
print(survey_data)
else:
print(f"Error getting survey data: {response.status_code}")
print(f"Error getting survey data: {response.raw}")
Final thoughts
Overall, automating how you work with Qualtrics survey data can save you time and effort, improve the accuracy and consistency of your data, and allow you to more easily and effectively analyse your survey results.
There are many other endpoints available in the Qualtrics API that allow you to access and manipulate survey data, including functions for creating and distributing surveys, managing responses, and analyzing data. You can find more information about these endpoints in the Qualtrics API documentation.