We plot this data into a histogram as shown below:
temperature = [27.3,29.5,26.4,24.,26.9,24.7,23.1,28.9,28.2,21.2,24.3,23.7,19.8,25.5,24.6,16.1,21.9,25.7,25.2,26.1,26.2,24.4,25.8,20.7,22.3,18.9,25.2,27.7,24.1,22.,26.2,25.5,20.1,24.,22.5,29.9,26.7,25.1,25.,26.7,28.,21.6,24.5,25.6,22.9,24.5,22.3,21.3,25.1,23.4,18.2,26.5,24.4,26.6,21.6,19.5,18.2,25.4,25.1,22.6,26.8,24.5,22.1,26.3,27.,24.7,23.5,26.4,24.8,24.6,24.1,18.8,23.6,20.3,25.3,23.3,20.8,21.7,22.2,25.9,24.2,23.4,23.6,26.1,24.9,23.7,26.9,20.5,31.1,24.8,29.2,20.8,25.3,23.4,25.7,23.2,28.7,26.,19.6,25.3 ]import matplotlib.pyplot as pltplt.hist(temperature, bins=20, facecolor='blue', edgecolor='black', alpha=0.7)plt.xlabel('temperature')plt.ylabel('frequency')plt.title('Temperature detection distribution')plt.show()
From this figure, we can clearly see the distribution of the data.
The temperature in this area is mostly between 24-26 degrees Celsius, which is comfortable. Occasionally there will be some low temperatures, and you need to prepare a few coats to keep warm.