It looks like you've uploaded a file, and I see that it contains data for the analysis you want to conduct in SPSS. I will first review the file to understand its structure and contents, and then help guide you through the steps you need to perform the tasks you mentioned. Let me take a look at the file. Let's inspect the contents of the uploaded file to understand its structure. file_path = '/mnt/data/1735000437782gh132emb.txt'

Read the file to examine its contents

with open(file_path, 'r', encoding='utf-8') as file: file_contents = file.readlines()

Display the first few lines to get an overview of the data

file_contents[:10] # First 10 linesThe data you provided appears to be tab-separated, with the following columns:

1. Year: Year of the observation.
2. City: The city name (e.g., Shanghai, Tianjin).
3. Per Capita Fixed Asset Investment (元/人): Per capita fixed asset investment (in yuan per person).
4. Labor Productivity (元/人): Labor productivity (in yuan per person).
5. High-Quality Product Rate (%): The percentage of high-quality products produced.
6. Technology Market Transaction/GDP (%): Technology market transaction as a percentage of GDP.
7. Per Capita Disposable Income (元/人): Per capita disposable income (in yuan per person).
8. Social Security and Employment Expenditure/Fiscal Expenditure (%): Proportion of fiscal expenditure on social security and employment.
9. Urban to Rural Disposable Income Ratio: Ratio of disposable income between urban and rural residents.
10. Disposable Income/GDP (%): Disposable income as a percentage of GDP.
11. Transportation, Storage, and Postal Industry GDP (%): Contribution of transportation, storage, and postal industry to GDP.
12. Road Length/Land Area (km/km²): Road length per square kilometer.
13. Road Freight Turnover (billion ton-km): Freight turnover by road.
14. Traffic Accident Death Rate (per 10,000 people): Traffic accidents resulting in death per 10,000 people.
15. Consumption Expenditure/GDP (%): Consumption expenditure as a percentage of GDP.
16. Urban Family Engel’s Coefficient (%): Engel's coefficient of urban families (percentage of income spent on food).
17. Non-Material Consumption Ratio (%): Non-material consumption as a percentage of total consumption.
18. E-commerce Sales/Social Retail Sales (%): E-commerce sales as a percentage of total retail sales.
19. Import and Export Trade/GDP (%): Import and export trade as a percentage of GDP.
20. Import-Export Trade Balance/Total Trade (%): The trade balance as a percentage of total import-export trade.
21. Foreign Direct Investment/GDP (%): Foreign direct investment as a percentage of GDP.
22. Outbound Direct Investment/GDP (%): Outbound direct investment as a percentage of GDP.
23. High-tech Imports/Total Imports (%): High-tech product imports as a percentage of total imports.
24. High-tech Exports/Total Exports (%): High-tech product exports as a percentage of total exports.

The data appears to span several years and cities, and it includes a wide variety of economic indicators for each city.

Next, I will guide you through the tasks you want to perform with SPSS:

1. Preprocessing the indicators: This includes normalization and standardization of the data.
2. Selecting a weighting method for the indicators and computing the composite score.
3. Creating statistical plots to analyze the development of the dual circulation economy.
4. Cluster analysis to explore spatial development differences using k-means or other clustering techniques.

Would you like me to proceed with more specific instructions for each step, or do you need further clarifications on the data?