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Reading Data from Text File in SPSS

Text files speak to another normal wellspring of information. Numerous spreadsheet projects and databases can spare their substance in one of numerous content record groups. Comma-or tab-delimited records allude to lines of information that utilization commas or tabs to show every factor. In this model, the information is tab-delimited.

1. From the menus pick:

Record > Import Data > Text Data

2. Go to the Samples\English envelope and select demo.txt.

The Text Import Wizard guides you through the way toward characterizing how the predetermined content document is deciphered.

Reading Data from Text File

Figure 1. Content Import Wizard: Step 1 of 6

3. In Step 1, you can pick a predefined design or make another arrangement in the wizard. Select No.

4. Click Next to proceed.

As expressed before, this document utilizes tab-delimited organizing. Additionally, the variable names are characterized on the top line of this document.

5. In stage 2 of the wizard, select Delimited to demonstrate that the record has a delimited arranging structure.

6. Select Yes to demonstrate that the record incorporates variable names at the highest point of the document.

7. Click Next to proceed.

8. In stage 3, enter 2 for the line number where the principal instance of information starts (since variable names are on the main line).

9. Keep the default esteems for the rest of this progression, and snap Next to proceed.

The Data see in Step 4 furnishes you with a fast method to guarantee that the document is perused effectively

Reading Data from Text File

11. Select Remove driving spaces for string esteems. Spaces toward the beginning of string esteems influence how string qualities are assessed in articulations. In this document, a few qualities for Gender have driving spaces that are not part of the worth. On the off chance that you don't expel those spaces, an estimation of " f" is treated as an unexpected incentive in comparison to "f".Figure 2. Content Import Wizard: Step 4 of 6

12. Click Next to proceed.

Since the variable names are adjusted to fit in with naming guidelines, stage 5 offers you the chance to alter any unfortunate names.

Information types can be characterized here too. For instance, you can change Income to dollar money position.

To change an information type:

13. In the Data review, select Income.

14. Select Dollar from the Data configuration drop-down list.Figure 3. Change the information type

The variable MaritalStatus contains both string and numeric qualities. Under five percent of the qualities are strings. With the default setting of 95% for Percentage of qualities that decide the Automatic information group, the variable is treated as numeric and the string esteems are set to framework missing. On the off chance that no information arrangement meets the rate esteem, the variable is treated as a string variable. In the event that you change the setting to 100, all qualities are saved, yet all numeric qualities are treated as strings.

15. Click Next to proceed.

16. Leave the default determinations in the last advance, and snap Finish to import the information

Reading Data from Text File

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