[pandas] DO IT 데이터분석을 위한 판다스 입문 (그래프2)

import seaborn as sns

tips = sns.load_dataset('tips')
print(tips.head())
print(type(tips))

%matplotlib notebook 
import matplotlib.pyplot as plt

fig = plt.figure()
axes1 = fig.add_subplot(1, 1, 1)

axes1.hist(tips['total_bill'], bins=10)
axes1.set_title('Histogram of Total Bill')
axes1.set_xlabel('Frequency')
axes1.set_ylabel('Total Bill')

 

scatter_plot = plt.figure()
axes1 = scatter_plot.add_subplot(1, 1, 1)
axes1.scatter(tips['total_bill'], tips['tip'])
axes1.set_title('Scatterplot of Total Bill vs Tip')
axes1.set_xlabel('Total Bill')
axes1.set_ylabel('Tip')

boxplot = plt.figure()
axes1 = boxplot.add_subplot(1, 1, 1)

axes1.boxplot([tips[tips['sex'] == 'Female']['tip'],
               tips[tips['sex'] == 'Male']['tip']],
               labels=['Female', 'Male'])
axes1.set_xlabel('Sex')
axes1.set_ylabel('Tip')
axes1.set_title('Boxplot of Tips by Sex')

def recode_sex(sex):
    if sex == 'Female':
        return 0
    else:
        return 1

tips['sex_color'] = tips['sex'].apply(recode_sex)

scatter_plot = plt.figure()
axes1 = scatter_plot.add_subplot(1, 1, 1)
axes1.scatter(
    x = tips['total_bill'],
    y = tips['tip'],
    s = tips['size'] * 10,  # 점의 크기
    c = tips['sex_color'],  # 점의 색상
    alpha = 0.5
)