#question 1
#please define and visualize the following function using python
# y= x^2 + 2*x + 6
#hint linspace()
# input variable [0,20]: 50 data points across
#purple line

import numpy as np
import matplotlib.pyplot as plt

$$ y= x^2+2*x+6 $$

x=np.linspace(0,20,50)
y=x**2+2*x+6
plt.figure(figsize=(5,3))
plt.plot(x,y, color= 'purple', linewidth=3)
plt.show()

#question 2
#load and read student data
#explore the distribution of test_preparation_course
#set different colors to dfferent groups

import pandas as pd
import seaborn as sns
df=pd.read_csv('student.csv')
df.head()

	gender	ethnicity	parental_education	lunch	test_preparation_course	math_score	reading_score	writing_score
0	female	group B	bachelor's degree	standard	none	72	72	74
1	female	group C	some college	standard	completed	69	90	88
2	female	group B	master's degree	standard	none	90	95	93
3	male	group A	associate's degree	free/reduced	none	47	57	44
4	male	group C	some college	standard	none	76	78	75

plt.figure(figsize=(5,3))
sns.countplot(data= df, x= 'test_preparation_course', hue= 'test_preparation_course',
              palette={'none':'steelblue','completed':'red'})
plt.show()

#question 3
#use visualization to explore which group
 #(text_preparation_course: none/completed) has better reading_score

sns.catplot(data= df, x='test_preparation_course', y='reading_score', kind= 'box', hue= 'test_preparation_course',
            palette={'none':'steelblue', 'completed': 'red'}) #could of used kind='violin' too
plt.show()