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17 changes: 17 additions & 0 deletions 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()
14 changes: 14 additions & 0 deletions 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.