Guac and Graphs: Exploring Avocado Sales through Visualizations

This activity involves visualizing data related to avocado sales volume per region. Carry out the following steps:

• Start by grouping the DataFrame by region.

• Calculate the sum of avocados sold for each region and then reset the index of the resulting DataFrame.

• Order the regions by their total volume in descending order and exclude TotalUS to focus on individual regions.

• Represent the processed data in a bar chart where the x-axis denotes the regions and the y-axis indicates the total volume of sales.

Use the following parameters while plotting:

Figure size : 12 by 8

Color : teal

Title: Total Volume of Avocados Sold by Region

xticks rotation : 90

Group the DataFrame by year to calculate the average of the AveragePrice of avocados for each year. Once you have that, create a line plot with the years on the x-axis and the average AveragePrice on the y-axis. Use the following information for your plot:

Figure size : 10 by 6

Colour : blue

Title: Average Price of Avocados by Year

markers : 'o'

linestyle : '-'

Finally, add gridlines to help visualize the changes in price more clearly, and then display your plot.

Begin by setting up your figure, ensuring to control the size of the plot to 10 by 6. Next, create a histogram to visualize how the average price of avocados is distributed. It is important to specify the number of bins - in this case, 10 - to break down the data. Choose colors that make the bars stand out, skyblue for the bars and black for the edges. Be sure to add labels to your axes and a title - Distribution of Average Price - so as to make clear what the histogram represents. Finally, include some gridlines along the y-axis for easier reading, with a linestyle of '--' and alpha setting of 0.7. Go ahead and display your plot to see how the prices are spread out.

First, calculate the total volume for each avocado type 4046, 4225, and 4770 by summing up their respective columns. Use these totals to create a pie chart that shows the proportion each type contributes to the overall volume using the information below:

Figure size : 8 by 8

Colours : #66c2a5, #fc8d62, #8da0cb

labels : '4046', '4225', '4770'

Title: Proportion of Total Volume for Each Avocado Type

autopct : %1.1f%%

startangle : 140

Finally, set the axis to be equal so your pie chart stays perfectly circular, then display it to see the breakdown of avocado types.

Figure size : 10 by 6

Colour : green

Title: Scatter Plot of Total Volume vs. Average Price

Group the DataFrame by the type column and sum the Total Volume for each avocado type (organic and conventional) . Then Plot a bar chart with the avocado types on the x-axis and their corresponding total sales volumes on the y-axis, using the following details:

Figure size : 10 by 6

Title : Total Volume of Avocados Sold by Type

colors : #1f77b4, #ff7f0e

Finally, use plt.show() to display your completed chart.

First, extract the unique years from the dataset and define the width of the bars and their positions on the x-axis. You then create a figure and axis for plotting. Next, you plot three sets of bars, each representing the total sales of a different type of avocado bag (Small Bags, Large Bags, and XLarge Bags) for each year. To calculate these totals, you use the groupby function on the DataFrame, grouping the data by the year column and summing the sales for each bag type. This ensures that the bars represent the aggregated sales for each year. To distinguish between the bag types, the bars are color-coded: blue for Small Bags (left of center), green for Large Bags (centered), and red for XLarge Bags (right of center). Adjust the positions of the bars to avoid overlap. Customize the plot with a title, x-axis and y-axis labels, and a legend. Finally, display the plot with a tight layout to ensure everything fits well.

Figure size : 10 by 6

Title : Volume of Different Bag Sizes Over the Years

colors : Small Bags ='blue', Large Bags='green', 'XLarge Bags='red'

Plot a time series chart showing daily average prices. Your task would include:

• Adding a horizontal line representing the overall average price.
• Adding annotations that marks the highest and lowest points on the graph.

Start by grouping the data by year and calculating the average price of avocados for each year. This creates a series where each year is associated with its average price. You then identify the years with the highest and lowest average prices to highlight these key points.

Then create a line graph of these yearly average prices, using the following information:

Figure size : 10 by 6

Colour : blue

label : 'Yearly Average Price'

marker: 'o'

linestyle: '-'

Horizontal line representing the overall average price

color: 'red'

linestyle : '--'

label : 'Overall Average Price'

Annotation of the maximum point

• Text : {max_price:.2f}

• Position: xy (max_year, max_price). Use xytext to position the text slightly above the point, (max_year, max_price + 0.05).

• Arrow Properties: arrowprops=dict(facecolor='green', shrink=0.05)

• Text Color: 'green' to match the text color with the arrow for consistency.

• Text Alignment: ha='center' to center the text horizontally over the point.

Annotation of the minimum point

• Text : {min_price:.2f}

• Position: xy (min_year, min_price). Use xytext to position the text slightly below the point, (min_year, min_price - 0.05).

• Arrow Properties: arrowprops=dict(facecolor='red', shrink=0.05)

• Text Color: 'red' to match the text color with the arrow for consistency.

• Text Alignment: ha='center' to center the text horizontally over the point.