Compare across forks

plot.py

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+import pandas as pd
+import matplotlib.pyplot as plt
+import numpy as np
+
+df = pd.read_csv('istherecorrelation.csv', sep = ';')
+df["WO [x1000]"]=df["WO [x1000]"].str.replace(',','.')
+df["WO [x1000]"]=pd.to_numeric(df["WO [x1000]"],errors = 'coerce')
+
+fig, ax1 = plt.subplots()
+
+x = df['Year']
+y1 = df['WO [x1000]']
+y2 = df['NL Beer consumption [x1000 hectoliter]']
+
+color = 'tab:red'
+ax1.set_xlabel('Year')
+ax1.set_ylabel('WO [x1000]', color=color)
+ax1.plot(x, y1, color=color)
+
+ax2 = ax1.twinx()  # instantiate a second axes that shares the same x-axis
+
+color = 'tab:blue'
+ax2.set_ylabel('Beer consumption [x1000 hectoliter]', color=color)  # we already handled the x-label with ax1
+ax2.plot(x, y2, color=color)
+
+fig.tight_layout()  # otherwise the right y-label is slightly clipped
+
+plt.show()
+
+fig.savefig('Beer consumption and WO.jpg',
+            format='jpeg',
+            dpi=300,
+            bbox_inches='tight')

solution_.md

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+# Papers
+1. MCC Van Dyke et al., 2019. The Rise of Coccidioides: Forces Against the Dust Devil Unleashed
+2. JT Harvey, Applied Ergonomics, 2002. An analysis of the forces required to drag sheep over various surfaces
+3. DW Ziegler et al., 2005. Correlation of continuous cardiac output measured by a pulmonary artery catheter versus impedance cardiography in ventilated patients
+
+Beer consumption and WO over time
+![alt text](https://github.com/mercylyn/CS_Assignment/blob/master/Beer%20consumption%20and%20WO.jpg)
+
+The graph above shows the number of students in WO (higher education) and beer consumption between the years 2006 and 2018. There is a clear upward trend from 2013 until 2018 in both students in WO and beer consumption.