Important changes in surface air temperature (SAT) have been reported over the years, including changes in global mean values, in the amplitude of the seasonal cycles, and in the occurrence of extreme fluctuations. This project is aimed at studying common data analysis methods, applying these methods to SAT data, and analyzing two datasets to contrast the magnitude of SAT changes in specific geographical locations. In this project, I analyzed the SAT data of Beijing and Jakarta by univariate analysis methods, and got their characteristics by comparing them. I extracted SAT data of 34 provincial capital cities in China from the dataset and used them to calculate the Pearson efficient between cities to construct a climate network for 34 cities. I calculated the SAT Shannon entropy value in East Asia. By comparing my own results with the results of the previous work and comparing the results in different periods, I discovered some climate changes that occurred in East Asia and found some erroneous data points that might exist in the dataset.