SPSS is a statistical analysis software used for data processing, analysis, and visualization. It provides a range of statistical analysis tools that facilitate researchers and analysts in extracting information, making decisions, and discovering patterns from data. Before conducting SPSS data calculations and analysis, researchers usually use the SPSS data transposition method to perform row column swaps on complex data, which is suitable for various forms of data text such as EXCEL, CSV, text data, SAS, etc., making it easier for researchers to have a clear and comprehensive understanding of data information.
What does SPSS data transposition mean?
If we want to rotate existing data tables, or to reconcile and swap rows and columns of tables, we can consider using SPSS data transposition method for fast processing. This method is suitable for various forms of data text such as EXCEL, CSV, text data, SAS, etc.
The following figure shows the data of entertainment sports projects carried out in Ankang Community, including the amateur competitive performance of community residents of different age groups in three aspects: color block recognition time (s), forward bending training distance (cm), and barbell weight (kg).
Figure 1: Entertainment and Sports Activities in Ankang Community
Data transposition can convert horizontal data into vertical data. Based on the case in this article, horizontal data can be understood as placing the measurement values of different participants in the same field into multiple variables, while vertical data is placing the measurement values of different participants in the same field into one variable.
Figure 2: Original horizontal data
3. Next, go to the application toolbar at the top of the SPSS editing window, count from left to right, and the data mode is located on the fourth button in the first row. Click and select the transpose option.
Figure 3: Find the editing function for transposition
Based on the entertainment and sports data of Ankang Community, we set the transposition standard as the participant number, so we put the number in the content box of the name variable. The transposition function generally only allows one variable as the transposition standard, and other variables automatically convert horizontal data to vertical data. Afterwards, we put age, color block recognition time (s), forward bending training distance (cm), and barbell weight (kg) into the content box of the transposed variables.
Figure 4: Contestant number as transposition standard
How to transpose SPSS data?
By clicking on the data module in the SPSS editing window, we can confirm the name variables in the transpose and move all the variables that need to be transposed. This enables us to set up the SPSS data transposition function. In addition to the above operation process, we can also view the types, labels, decimal places, and other information of data variables in the SPSS variable view to determine whether further adjustments are needed to variable names, variable types, and other information.
According to the above steps, we obtained the re transposed data of Ankang community entertainment and sports projects. The following figure shows the data view after SPSS data transposition, with only five groups: age, color block recognition time (s), forward bending training distance (cm), barbell weight (kg), and gender. K1 to K20 represent the participant numbers from number 1 to number 20.
Figure 5: Transposed Vertical Data
2. Continuing to look at the variable view of the case, we can see the variable data named K1 to K20, which indicates that data transposition has been achieved through the operation of SPSS functionality application.
Figure 6: Variables from K1 to K20
3. In addition, we can also query the specific program situation on the output page. The serial number has been used to define new transposed variables, with names K1 to K20. The transposed new dataset is all included in SPSS dataset 4.
Figure 7: Viewing transposed SPSS program
SPSS has a user-friendly graphical menu driven interface, which is easy to operate. Users do not need programming skills and can complete most operations through menus, buttons, and dialog boxes, reducing the threshold for use. SPSS has powerful functions, covering data management, descriptive statistics, mean comparison, regression analysis, cluster analysis, factor analysis, time series analysis, and many other statistical analysis processes, which can meet the diverse analysis needs of different users from basic to advanced.
