Week 16 Homework

Homework.py

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+import pandas as pd
+import statistics
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+food_consumption = pd.read_csv('/Users/Sansar/Desktop/DS Documents/MathStats-Module-Week16/food_consumption.csv', index_col=0)
+print(food_consumption.head())
+print()
+
+#####################################################################################################################################
+
+be_consumption = food_consumption[food_consumption['country'] == 'Belgium']
+
+mn1 = statistics.mean(be_consumption['consumption'])
+print(mn1)
+
+md1 = statistics.median(be_consumption['consumption'])
+print(md1)
+print()
+
+usa_consumption = food_consumption[food_consumption['country'] == 'USA']
+
+mn2 = statistics.mean(usa_consumption['consumption'])
+print(mn2)
+
+md2 = statistics.median(usa_consumption['consumption'])
+print(md2)
+print()
+
+
+#####################################################################################################################################
+
+rice_consumption = food_consumption[food_consumption['food_category'] == 'rice']
+plt.hist(food_consumption['co2_emission'], bins=30)
+plt.show()
+print()
+
+
+#####################################################################################################################################
+
+rice_consumption = food_consumption[food_consumption['food_category'] == 'rice']
+
+rice_mean = statistics.mean(rice_consumption['co2_emission'])
+rice_median = statistics.median(rice_consumption['co2_emission'])
+
+df = pd.DataFrame(
+    {
+        "Mean" : [(rice_mean)], '| '
+        "Median" : [(rice_median)]
+    }
+)
+
+print(df)
+print()
+
+#####################################################################################################################################
+
+co2_emission = food_consumption['co2_emission'] 
+x = np.quantile(co2_emission, np.linspace(0, 1, 6))
+print(x)
+print()
+
+#####################################################################################################################################
+
+food_category = food_consumption['food_category']
+
+co2_var = food_consumption.groupby('food_category')['co2_emission'].var()
+co2_std = food_consumption.groupby('food_category')['co2_emission'].std()
+
+data = {'co2_var': co2_var,
+        'co2_std': co2_std}
+
+df = pd.DataFrame(data)
+print(df)
+print()
+
+#####################################################################################################################################
+
+co2_beef = food_consumption[food_consumption['food_category'] == 'beef']
+plt.hist(food_consumption['co2_emission'], bins=30)
+plt.show()
+print()