United State, remains the largest global economic system, plays a very important role in maintaining the stability of international monetary market, the every small change in American Finance could trigger butterfly effect in international world. So it would be very necessary for us to find and learn the phenomenon and rule from megadata. On this paper, I would use data visualization (and dynamic visualization as much as possible) to make the exhibition.
Figure 1 2007-2017 USA Umemployment Rate
Figure 1 demonstrates that USA unemployment rate has improved since 2007 or earlier, and it reaches the top in 2010, which was the year after the 2009 outbreak of American financial crisis, though it was the highest peak among the 2007-2017’s UR(Unemployment data), however, the flat slope line reflect the hysteresis effect of this disaster. After the 2010, the UR has gradually descended and finally under the world unemployment rate line in 2015. Up to 2017, the American UR still has a downtrend. In 4th June,2018, the FED(the Federal Reserve) publish the newest official unemployment rate, and it has fell to 3.8%, which is the lowest value since 2000.
Figure 2 The Change of USA State Unemployment Rate(GIF)
Figure 2 is a dynamic visualization map, demonstrating the UR change of USA state Among 2007, 2009, 2015 and 2017. Due to the particularity of Puerto Rico, the map remove both the geographical and digital data of it, so the whole map would only includes the 51 states of America. This map graph shows that North&South Dakota and Nebraska state have relatively low UR, even in the year of financial crisis they still stay stable, it could relates to its highly developed agricultural system, this system make sure that once the international financial market suffer a depression, this three states could have a less negative impact .Besides, the Michigan state had the big change during the crisis, maybe because of its intense industrialization of automobile. And it also could see that the states UR come to lower in 2017 than it in 2007.
Figure 3 2007-2017 USA Civilian Labor Force And Growth Rate
Figure 3 shows the growth of USA civilian labor force and its growth rate curve, the steep slope between 2008 and 2009 demonstrates the depression of labor market and it also could explain why the unemployment rate would reach a peak in poor economic environment. The growth rate curve keeps fluctuating and up to 2017 it stills haven’t recover to the value which it reached in 2008.
Figure 4 2017 USA States Civilian Labor Force Rate
Figure 4 illustrates the proportion of USA civilian labor rate and it can tell from the graph that the California state has the most proportion and the Texas stay the second. California is the one of the most developing state in USA, in 2018, its real GDP achieved to the growth rate of 3.4%, and total amout of 2.747 trillion, its economy of scale has surpassed Britain and become the World’s fifth economic entity.
The difficulty of data visualization is how to find out the relevance and rule behind the mass data, and making analysis of it, I think the domestic data environment still needs to be improved, at least in the part of data collection and public. Besides, the most important of data visualization is not making a coolest picture but making a lucid graph.
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