16494105 Assignment Submission

Plot_Assingment.py

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+import pandas as pd
+import matplotlib.pyplot as plt
+
+# Load CSV
+df = pd.read_csv("istherecorrelation.csv", sep=';')
+
+# Extract data
+years = df.iloc[:, 0].astype(int)
+wo = df.iloc[:, 1].str.replace(',', '.').astype(float)
+nl = df.iloc[:, 2].astype(float)
+
+wo_lag1 = wo.shift(1)
+nl_lag1 = nl.shift(1)
+
+# Create dual-axis plot
+fig, ax1 = plt.subplots(figsize=(10,6), dpi=300)
+# Left axis: WO
+ax1.plot(years, wo, marker='o', color='blue', alpha=0.5, label='WO [x1000]')
+ax1.set_xlabel("Year")
+ax1.set_ylabel("WO [x1000]", color='blue')
+ax1.tick_params(axis='y', labelcolor='blue')
+ax1.set_ylim(wo.min()*0.95, wo.max()*1.05)
+
+# Right axis: NL Beer consumption
+ax2 = ax1.twinx()
+ax2.plot(years, nl, marker='s', color='green', alpha=0.5, label='NL Beer consumption [x1000 hl]')
+ax2.set_ylabel("NL Beer consumption [x1000 hl]", color='green')
+ax2.tick_params(axis='y', labelcolor='green')
+ax2.set_ylim(nl.min()*0.95, nl.max()*1.05)
+
+# Add Legend
+lines_1, labels_1 = ax1.get_legend_handles_labels()
+lines_2, labels_2 = ax2.get_legend_handles_labels()
+ax1.legend(lines_1 + lines_2, labels_1 + labels_2, loc='upper left')
+
+
+plt.title("WO and NL Beer Consumption over Time ")
+plt.xticks(years, rotation=45)
+plt.grid(True)
+plt.tight_layout()
+
+# Save plot
+plt.savefig("plot.png", dpi=300)
+plt.show()
+
+print("Correlation WO vs NL same year:", wo.corr(nl))
+print("Correlation WO vs NL previous year:", wo.corr(nl_lag1))
+print("Correlation NL vs WO previous year:", nl.corr(wo_lag1))
+

signment solution Markdown file, plot, and script

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+diff.astextplain.textconv=astextplain
+filter.lfs.clean=git-lfs clean -- %f
+filter.lfs.smudge=git-lfs smudge -- %f
+filter.lfs.process=git-lfs filter-process
+filter.lfs.required=true
+http.sslbackend=openssl
+http.sslcainfo=C:/Program Files/Git/mingw64/etc/ssl/certs/ca-bundle.crt
+core.autocrlf=true
+core.fscache=true
+core.symlinks=false
+pull.rebase=false
+credential.helper=manager
+credential.https://dev.azure.com.usehttppath=true
+init.defaultbranch=master
+gui.recentrepo=C:/Users/kstha/Desktop
+core.repositoryformatversion=0
+core.filemode=false
+core.bare=false
+core.logallrefupdates=true
+core.symlinks=false
+core.ignorecase=true
+submodule.active=.
+remote.origin.url=https://github.com/KsThakoerdin/CS_Assignment.git
+remote.origin.fetch=+refs/heads/*:refs/remotes/origin/*
+branch.main.remote=origin
+branch.main.merge=refs/heads/main
+user.name=Kevin Thakoerdin
+[email protected]

solution_16494105.md

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+# CS Toolbox Assingment
+
+**Name :** Kevin Thakoerdin
+
+**Student ID :** 16494105
+
+## Papers:
+
+1. MCC Van Dyke et al., 2019
+2. JT Harvey, Applied Ergonomics, 2002
+3. DW Ziegler et al., 200
+
+## Plot
+
+![My plot](plot.png)
+
+## Analysis
+
+The computed correlation between WO and NL Beer consumption measures a linear association. However, by visual inspection, the NL Beer consumption series does not follow a linear trend: it remains roughly steady until 2014 and then rises sharply, almost exponentially. In contrast, the WO student population increases steadily over the entire period. This suggests that a simple linear regression would not fit NL Beer consumption well, and the high correlation mainly reflects the late increase rather than a consistent relationship throughout. Therefore, while correlation gives a first indication of association, it does not fully capture the temporal dynamics of the data