U.S. Budget: Where the Money Went

Create a bar chart with the created DataFrame top_5_departments to display the budget allocation for these top 5 departments using the following parameters :

Figuresize : 10 by 6

Colors : Defined in notebook

Title : Top 5 U.S. Departments by Budget Allocation in 1962

xlabel : Department

ylabel : Budget (in Millions)

Rotate the x-label by 45 degrees to ensure better readability, then use fig.tight_layout() to ensure everything fits perfectly.

Use the created DataFrmae combined_budget (which combines the inflation adjusted budget for the defense department and other departments) to plot a stacked bar chart using the following parameters:

Figure size : 10 by 6

Colors : blue and lightgray

Title : Proportion of Department of Defense vs. Other Departments (1962-2018), fontsize=16

xlabel : Fiscal Year, fontsize=12

ylabel : Budget Dollars (Inflation Adjusted), fontsize=12

Legend Title : Department, loc=upper left

Finish by displaying your plot to see the budget proportions over time.

In this exercise, you'll create a clear visualization that compares the original and inflation-adjusted budget values by fiscal year. You will be using Matplotlib's object-oriented interface to create two vertically aligned subplots sharing a common x-axis figure size of 12 by 10.

Subplot 1 will display the original budget values with a bar chart in skyblue.

• Add a title: Original Budget Dollars by Fiscal Year

• Label the y-axis as: Budget Dollars

Subplot 2 will showcase the inflation-adjusted budget values with a bar chart in salmon.

• Add a title: Inflation Adjusted Budget Dollars by Fiscal Year

• Label the y-axis as: Inflation Adjusted Budget Dollars

• Rotate the x-axis labels by 45 degrees, and label the x-axis as: Fiscal Year

Finally, apply tight_layout() to ensure the layout is well-adjusted and clear.

Create a stacked bar chart with the created DataFrame pivot_data by iterating over the departments and stacking the bars and adjusting the bottom parameter to accumulate the heights. Use the following parameters for the plot :

Figure size : 12 by 8

Title : Proportion of Each Department's Budget Relative to Total Budget

xlabel : Fiscal Year

ylabel : Proportion of Total Budget

Legend Title : Department or Unit

Ensure that your x-axis labels are rotated at 45 degrees for readability. Lastly, apply the tight_layout() function to fine-tune the layout before displaying the plot.

Plot the predefined proportions in your notebook to plot a donut chart using the following parameters:

Figure size : 8 by 8

Colors : Defined in Notebook

Title: Proportion of Total Federal Budget Allocated to Branches

Use autopct to display the percentage values inside the chart with the format %1.1f%%

Set the start angle to 140 degrees for proper orientation.

Insert a white circle at the center with coordinates (0, 0) and a radius of 0.5 to create the donut effect. Adjust the appearance of the text labels (percentages) using the autotexts parameter, with font size = 10 and font weight = bold. Finally, use tight_layout() to ensure proper layout.

Create a horizontal bar chart with the DataFrame top_departments, setting the bars' color to green and a figure size of 10 by 6. Label the x-axis as Budget Dollars (Inflation Adjusted), the y-axis as Department or Unit, and give the chart the title Most-Funded Departments (Inflation Adjusted). Finally, apply tight_layout() to ensure the chart is neatly formatted.

In this exercise, you will analyze and visualize the top five funded departments based on their inflation-adjusted budgets for the years 1962 and 2018. You will use a bar chart to facilitate a direct comparison between the two years, highlighting how funding has changed over time. Using the calculated DataFrames top_2018 and top_1962, create a bar chart to compare the top five departments from both years.

Figure size : 10 by 6

Title : Top 5 Funded Departments (Inflation Adjusted) in 1962 vs 2018

xlabel : Departments

ylabel : Budget Dollars (Inflation Adjusted)

bar_width : 0.35

Adjust the x-ticks to display department names, rotating them by 45 degrees for better readability. Also, include a legend to distinguish between the years. Finally, Use .tight_layout() to ensure the layout is clean and free of overlaps.

Using the created DataFrame sorted_presidents, create a 12 by 8 figure and axis for plotting, then generate a dark blue bar chart, setting the x-axis to the sorted president names and the y-axis to their total budgets. Label the x-axis as President, the y-axis as Total Budget Dollars (Inflation Adjusted), and give the plot a title: Which President Had the Largest Inflation-Adjusted Budget?. Adjust x-tick labels to be readable by rotating them(rotation=45, ha=right), and use .tight_layout to ensure the plot is propoerly laid out. Finally, use idxmax() and max() to find and print the name and amount of the president with the highest budget.

Using the DataFrame df_agriculture created in your notebook, plot the percentage changes over fiscal years for each president.

Figure size : 12 by 6

Marker : o

Title : Percentage Change in Inflation-Adjusted Budget for the Department of Agriculture by President

xlabel : Fiscal Year

ylabel : Percentage Change in Budget Dollars (Inflation Adjusted)

Legend Title : President

Finally, add grid lines and display the plot using .tight_layout().