<jupyter_start><jupyter_text>An Analysis of Covid 19 in Germany ![germany_image](https://cdn.britannica.com/97/897-004-232BDF01/Flag-Germany.jpg)  Author Information IA 241: Final Project  Author: <NAME>  Data Source This data is from [European Center for disease and control](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide)<jupyter_code>%matplotlib inline
import pandas<jupyter_output><empty_output><jupyter_text>Quick overview of the Data<jupyter_code>df = pandas.read_excel('s3://mitch-ia241-2021spring/covid_data.xls')
df[:10]<jupyter_output><empty_output><jupyter_text>Germany's Data<jupyter_code>germany_data = df.loc[df['countriesAndTerritories'] == 'Germany']
germany_data[:10] #the top 10 rows<jupyter_output><empty_output><jupyter_text>Number of Confirmed Covid19 Cases in Germany as of December 2020<jupyter_code>germany_data.groupby('countriesAndTerritories').sum()['cases']
print("The number of confirmed cases in Germany since December of 2020 is 1,337,078. Germany has a relatively large population     consiting of over 83 million citizens, therfore a litte over a million cases is pretty low ")<jupyter_output>The number of confirmed cases in Germany since December of 2020 is 1,337,078. Germany has a relatively large population     consiting of over 83 million citizens, therfore a litte over a million cases is pretty low<jupyter_text>Number of Confirmed Deaths by Month<jupyter_code>month_deaths=germany_data.groupby('month').sum()['deaths']
month_deaths[:]<jupyter_output><empty_output><jupyter_text>Bar Graph Summarizing Confirmed Deaths per Month<jupyter_code>month_deaths.plot.bar()
print("According to the bar Graph, there was a spike in deaths during the month of April. Towards the end of the year,    there was a significant spike during the months of November and December.")
print("The month of November had the highest amount of deaths with 5796")<jupyter_output>According to the bar Graph, there was a spike in deaths during the month of April. Towards the end of the year,    there was a significant spike during the months of November and December.
The month of November had the highest amount of deaths with 5796<jupyter_text>Number of Confirmed Deaths in Relation to the Amount of Cases<jupyter_code>germany_data.plot.scatter(x='cases',y='deaths')<jupyter_output><empty_output><jupyter_text>Analysis<jupyter_code>print("After researching and compiling data from the Covid Database for the country of Germany, I noticed that despite    Germany's large population they had a low amount of cases with a total of 1,337,078 since December of 2020. Also   during the months of November and December they had a huge increase in confirmed deaths along with cases. I used a bar graph to illustrate the amount of deaths per month to make it easier to comprehend. I also used a scatter plot which represented values for the amount of cases and deaths. According to the scatterplot, their is a non-linear postive associtation with the amount of cases and confirmed deaths.")<jupyter_output>After researching and compiling data from the Covid Database for the country of Germany, I noticed that despite    Germany's large population they had a low amount of cases with a total of 1,337,078 since December of 2020. Also   during the months of November and December they had a huge increase in confirmed deaths along with cases. I used a bar graph to illustrate the amount of deaths per month to make it easier to comprehend. I also used a scatter plot which represented values for the amount of cases and deaths. According to the scatterplot, their is a non-linear postive associtation with the amount of cases and confirmed deaths.<jupyter_text>Limitations<jupyter_code>print("After the completion of this project, there was not really any limitations for this project other than the sample  size consiting of data from December 2020 up until present day.")<jupyter_output>After the completion of this project, there was not really any limitations for this project other than the sample  size consiting of data from December 2020 up until present day.
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