These datasets contain cleaned data survey results from the October 2021-January 2022 survey titled "The Impact of COVID-19 on Technical Services Units". This data was gathered from a Qualtrics survey, which was anonymized to prevent Qualtrics from gathering identifiable information from respondents. These specific iterations of data reflect cleaning and standardization so that data can be analyzed using Python. Ultimately, the three files reflect the removal of survey begin/end times, other data auto-recorded by Qualtrics, blank rows, blank responses after question four (the first section of the survey), and non-United States responses. Note that State names for "What state is your library located in?" (Q36) were also standardized beginning in Impact_of_COVID_on_Tech_Services_Clean_3.csv to aid in data analysis. In this step, state abbreviations were spelled out and spelling errors were corrected.

This dataset contains the cleaned data survey results from the October 2021-January 2022 survey titled "The Impact of COVID-19 on Technical Services Units". This data was gathered from a Qualtrics survey, which was anonymized to prevent Qualtrics from gathering identifiable information from respondents. The specific iteration of this data reflects the removal of survey begin/end times, as well as other data auto-recorded by Qualtrics. It does not reflect removed blank rows, surveys containing blank data after question four (the first survey section), and non-United States responses.

These datasets, clustered by library type, contain cleaned data survey results from the October 2021-January 2022 survey titled "The Impact of COVID-19 on Technical Services Units". This data was gathered from a Qualtrics survey, which was anonymized to prevent Qualtrics from gathering identifiable information from respondents. These specific iterations of data reflect the cleaning and standardization conducted on the raw dataset retrieved from survey responses, and then cluster the data into specific library type files. All files reflect the removal of data auto-generated by Qualtrics (such as survey start/stop times), blank rows, survey responses not completed after question four (the first section of survey questions), and non-United States responses. Survey respondents were asked to identify their library type (Academic, Public, K-12 School, Special Collections and/or Archives, Other, and Blank responses). There is some duplication between files, as respondents were allowed to select more than one library type to represent the sometimes complicated governing structure within libraries. Note that these files also contain an additional cleaning steps to standardize numbers within the "How many full and part-time staff members (not student workers) were on your Technical Services team prior to the COVID-19 pandemic?" and "How many full and part-time staff members (not student workers) are on your technical services team now?" questions (Q6 and Q7). String text was removed from these fields, as well as incomplete responses (e.g. Indicating a before number but not an after number).