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import matplotlib.pyplot as plt import seaborn as sns import pandas as pd # Your CAAR values and significance data = [ [0.386, 0.660, 0.471, 0.680, 1.64, 1.71, -0.32], [0.87, 1.15, 0.96, 1.17, 2.12, 2.20, 0.16], [1.36, 1.63, 1.44, 1.65, 2.61, 2.68, 0.65], [0.99, 1.26, 1.07, 1.28, 2.24, 2.31, 0.28], [-0.55, -0.27, -0.46, -0.25, 0.70, 0.78, -1.26], [-0.24, 0.03, -0.16, 0.05, 1.01, 1.08, -0.95], [-1.09, -0.82, -1.01, -0.80, 0.16, 0.23, -1.80] ] significance = [ ["***", "***", "***", "***", "***", "***", "*"], ["***", "***", "***", "***", "***", "***", ""], ["***", "***", "***", "***", "***", "***", "***"], ["***", "***", "***", "***", "***", "***", "*"], ["***", "***", "***", "***", "***", "***", "***"], ["***", "", "*", "", "***", "***", "***"], ["***", "***", "***", "***", "**", "**", "***"] ] index = [-10, -5, -4, -3, -2, -1, 0] columns = [0, 1, 2, 3, 4, 5, 10] # Create a DataFrame for the heatmap df = pd.DataFrame(data, index=index, columns=columns) annotations = df.astype(str) + '\n' + pd.DataFrame(significance, index=index, columns=columns) # Plotting the heatmap plt.figure(figsize=(12, 8)) heatmap = sns.heatmap(df, annot=annotations, fmt="", cmap="RdYlGn", center=0, linewidths=.5, cbar_kws={'label': 'CAAR'}) # Add titles and labels plt.title('CAAR and t-statistics from Event Study (Heat Map)') plt.xlabel(r'$\Gamma_2$') plt.ylabel(r'$\Gamma_1$') # Save the figure plt.savefig("CAAR_Heatmap.png") plt.show()
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