Calculating the Mean and Creating a Bar Chart Calculating the Mean of a Column In Python, the pandas DataFrame lets you easily compute summary statistics, such as the mean (average) of a column. This is done using the syntax: table['column'].mean() In the example below, we're computing the mean of the "number" column and printing it with a short label to help interpret the result. Visualizing Data with a Bar Chart The seaborn library allows you to create beautiful charts with very little code. Here, we use it to plot how each number maps to its square. The code: Prints the mean of the "number" column. Uses the seaborn library to create a bar chart, with: "number" on the x-axis "squared" values on the y-axis Adds labels, a grid, and styling for clarity. Your Task Run the code and observe the printed mean and the chart. Question: What is the mean of the "number" column? Can you visually confirm this number makes sense based on the data shown in the bar chart? print("Column 2 mean:", df['squared'].mean()) sns.set_theme(style="whitegrid") sns.barplot(data=df, x='number', y='squared') sns.despine() plt.grid(True, linestyle=':', linewidth=1) plt.title("Square of Numbers") plt.xlabel("Number") plt.ylabel("Squared Value") plt.show()