This mini project is once again about the Google Data Studio. You…
Question Answered step-by-step This mini project is once again about the Google Data Studio. You… This mini project is once again about the Google Data Studio.You have already earned a certificate on how to work with Google Data Studio. Here is your turn to use it in action.For this mini-project, feed the US STATE VACCINATION dataset (the same dataset as in your Assignment 11) into Google Data Studio (Hint: Connect to Data source, then, upload the CSV file). Then, Make one page report that compares the immunization between Texas and one other state. It can be the same state that you had picked for visualization with Bokeh in your Assignment 11. However, your report must feature at least two graphs: One graph that compares the number of people who are fully vaccinated, and the other that shows the rate (percentage) of the people who are fully vaccinated. Add enough descriptive elements on your report to make sure that it will be informative for the users.In addition, you must put a date-range filter somewhere on the page to allow the user to adjust the start and end dates for the report.Remember to use the correct sharing options for BOTH your data source AND your report. Also, remember to format your report appropriately based on what you have learned in this course, and also in the step-by-step tutorial that you already have the certificate for. (If you feel you need a refresher, it is okay to go through some steps of that tutorial again to better accomplish this task.)Bonus (10%): Add another element to your report that allows the user to change which states are compared on the report page. The given below is the question and answer of assignment11 for your helpImage transcription textFiltering Datasets Loaded from Files with Bokeh Dataset: us_state_vaccinations.csv in this exercise, we aim tocompare the RATE of fully vaccinated people in the state of Texas and another state from the 4B continentalUS states. To begin, download the most up-to-date dataset ?le from the Kaggle website, decompr… Show more… Show more# In[1]:# program to read the vaccination csv file plot the comparison of vaccination progress for Texas State with any other 48 States #importing required librariesimport pandas as pdfrom bokeh.plotting import figure, output_file, show#fetching data from csv to df pandas dataframedf = pd.read_csv(“us_state_vaccinations.csv”)# In[2]:#filtering columns for plotting purposetemp_df = df[[‘date’, ‘location’,’people_fully_vaccinated_per_hundred’,’people_fully_vaccinated’]]#list of statesprint(temp_df[‘location’].unique())# In[3]:#plotting “Comparison of ‘people_fully_vaccinated’ for Texas state and New York State”#setting x values from date column with filtering texas x = list(pd.to_datetime(temp_df[temp_df[‘location’]==’Texas’][‘date’], infer_datetime_format=True))#setting y values for Texas from people_fully_vaccinated columny = list(temp_df[temp_df[‘location’]==’Texas’][‘people_fully_vaccinated’])#setting x values from date column with filtering New York x2 = list(pd.to_datetime(temp_df[temp_df[‘location’]==’New York State’][‘date’], infer_datetime_format=True))#setting y values for New York from people_fully_vaccinated columny2 = list(temp_df[temp_df[‘location’]==’New York State’][‘people_fully_vaccinated’])#initialising the plot with bokeh figureplot = figure(width=800, height=250, x_axis_type=”datetime”,x_axis_label=’date’,y_axis_label=’people_fully_vaccinated’,title=”Comparison of people_fully_vaccinated for Texas state and New York State”)#plot for Texasplot.step(x = x, y = y, color =’green’,legend_label=’Texas’)#plot for NewYorkplot.step(x = x2, y = y2, color =’red’,legend_label=’New York’)#setting legend locationplot.legend.location = “top_left”#showing plotshow(plot)# In[4]:#plotting “Comparison of ‘people_fully_vaccinated_per_hundred’ for Texas state and New York State”#setting x values from date column with filtering texas x = list(pd.to_datetime(temp_df[temp_df[‘location’]==’Texas’][‘date’], infer_datetime_format=True))#setting y values for Texas from people_fully_vaccinated_per_hundred columny = list(temp_df[temp_df[‘location’]==’Texas’][‘people_fully_vaccinated_per_hundred’])#setting x values from date column with filtering New York x2 = list(pd.to_datetime(temp_df[temp_df[‘location’]==’New York State’][‘date’], infer_datetime_format=True))#setting y values for New York from people_fully_vaccinated_per_hundred columny2 = list(temp_df[temp_df[‘location’]==’New York State’][‘people_fully_vaccinated_per_hundred’]) #initialising the plot with bokeh figureplot = figure(width=800, height=250, x_axis_type=”datetime”,x_axis_label=’date’,y_axis_label=’people_fully_vaccinated_per_hundred’,title=”Comparison of ‘people_fully_vaccinated_per_hundred’ for Texas state and New York State”)#plot for Texasplot.step(x = x, y = y, color =’green’,legend_label=’Texas’)#plot for NewYorkplot.step(x = x2, y = y2, color =’red’,legend_label=’New York’)#setting legend locationplot.legend.location = “top_left”#showing plotshow(plot) Computer Science Engineering & Technology Python Programming IT CSE6 Share QuestionEmailCopy link Comments (0)
