1. Gives clear instructions about how to run your analysis (it might be short!);
2. Explains what does or doesn’t work in your project;
3. Includes a 1-paragraph reflection about your experience with the project.
4. Includes a 1-paragraph reflection on what you learned from the results of your analyses.
    (Did you learn anything about climate or data analysis?)


1. To run my phase2.py analysis, type "plot_yearly_snow()" into the Python Shell and hit enter!

2. Each function in this project works properly.

3. This project was extremely challenging for me, and pushed me outside of my comfort zone in ways that I had not
been earlier this semester. Figuring out how to deal with very large data sets in a timely fashion and configure
dictionaries did not come intuitively, but as I worked with them more and more I realized that being able to handle
these amounts of data in this fashion is extremely useful. I decided to change my part 2, as I realized that my initial
proposal did not show any significant or interesting data. I instead decided to analyze the days of snowfall per year
in my home state, New York, as this is more quantifiable and shows more tangible results in my visual representation. My hypothesis going into
this phase2 was that the number of days of snowfall per year would decrease, on average, from 1869 to now, in comparison to the average yearly
temperature, which appeared to pretty steadily increase from 1869 to now in my part one data.

4. From my analysis, I learned that there is an average of 10-20 days of snow in New York each year. There was one outlier in 1916 when it snowed 30 days in the year, but other than that, the snowfall has been fairly consistent. Since 1996, it has not snowed 20 or higher days in the year and the number of days of snowfall has stabilized around a lower number. I believe that my findings generally support my initial hypothesis as the highest peaks in my bar graph “plot_yearly_snow()” tend to be more towards the earlier side of my data. This is interesting to me as I can check in on this pattern and see if these results hold true in the coming years as I continue to live in New York and evaluate the climate changes. I would venture to say that my data correlates with the average yearly temperatures, which have been trending upwards over the past 150 years, and I think that together, these graphs would indicate some form of climate change and perhaps warming in New York from 1869 to the present.