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diff --git a/plot.py b/plot.py
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+import pandas as pd
+import matplotlib.pyplot as plt
+
+df = pd.read_csv("istherecorrelation.csv", sep=";", decimal=",")
+df.columns = df.columns.str.strip()
+df["Beer consumption (/100)"] = df["NL Beer consumption [x1000 hectoliter]"] / 100
+
+plt.figure(dpi=300)
+plt.plot(df["Year"], df["Beer consumption (/100)"], marker="o", label="Beer consumption")
+plt.plot(df["Year"], df["WO [x1000]"], marker="s", label="Higher education enrollment")
+plt.xlabel("Year")
+plt.ylabel("Values - Beer (x1e5) & Enrollment (x1e3)")
+plt.title("Beer Consumption vs Enrollment in Higher Education (2006–2018)")
+plt.legend()
+plt.grid(True)
+plt.savefig("plot.png")
+plt.show()
diff --git a/solution_16076591.md b/solution_16076591.md
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+- Student Name - Pranav Bali
+- Student ID: 16076591
+
+## Key papers
+## Fantastic Yeasts and Where to Find Them: The Hidden Diversity of Dimorphic Fungal Pathogens (2019)
+**Authors:** Marley C.C. Van Dyke, Marcus M. Teixeira, Bridget M. Barker  
+**Journal:** *Current Opinion in Microbiology*  
+ - MCC Van Dyke et al., 2019
+ - JT Harvey, Applied Ergonomics, 2002
+ - DW Ziegler et al., 2005
+
+![Plot](plot.png)
+
+There is a good correlation between the number of enrolled students and beer consumption as we can see that increasing enrolment, increased the beer consumption by a lot.