import numpy as np import matplotlib.pyplot as plt

创建画布和子图

fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 5))

设置x轴范围和步长

x = np.arange(-np.pi, np.pi, 0.01)

画sinx的函数图像

ax1.plot(x, np.sin(x), linewidth=2.5) ax1.set_xlabel('x') ax1.set_ylabel('sin(x)') ax1.set_title('Sin(x) Function')

画cosx的函数图像

ax2.plot(x, np.cos(x), linewidth=2.5) ax2.set_xlabel('x') ax2.set_ylabel('cos(x)') ax2.set_title('Cos(x) Function')

显示图像

plt.show()

import pandas as pd import matplotlib.pyplot as plt

读取数据

data = pd.read_excel('a.xlsx')

统计每个地区的酒店数量

hotel_counts = data['地区'].value_counts()

创建画布和子图

fig, ax = plt.subplots(figsize=(10, 5))

画柱状图

ax.bar(hotel_counts.index, hotel_counts.values, color='red')

设置横轴标签旋转90度

plt.xticks(rotation=90)

显示柱子上方的数值

for x, y in zip(hotel_counts.index, hotel_counts.values): ax.text(x, y, str(y), ha='center', va='bottom')

设置标题、横轴标签、纵轴标签

ax.set_title('Hotel Counts by Region') ax.set_xlabel('Region') ax.set_ylabel('Counts')

显示图像

plt.show()

import pandas as pd import matplotlib.pyplot as plt

读取数据

data = pd.read_excel('a.xlsx')

统计每个价格等级的酒店数量

hotel_counts = data['价格等级'].value_counts()

创建画布和子图

fig, ax = plt.subplots(figsize=(10, 5))

画柱状图

ax.bar(hotel_counts.index, hotel_counts.values)

显示柱子上方的数值

for x, y in zip(hotel_counts.index, hotel_counts.values): ax.text(x, y, str(y), ha='center', va='bottom')

设置标题、横轴标签、纵轴标签

ax.set_title('Hotel Counts by Price Level') ax.set_xlabel('Price Level') ax.set_ylabel('Counts')

显示图像

plt.show()

import pandas as pd import matplotlib.pyplot as plt

读取数据

data = pd.read_excel('a.xlsx')

统计每个价格等级的酒店数量

hotel_counts = data['价格等级'].value_counts()

计算每个价格等级的占比

hotel_percent = hotel_counts / hotel_counts.sum()

创建画布和子图

fig, ax = plt.subplots(figsize=(8, 8))

画饼图

ax.pie(hotel_counts.values, labels=hotel_counts.index, autopct='%1.1f%%')

设置标题和图例

ax.set_title('Hotel Proportion by Price Level') ax.legend(hotel_counts.index)

显示图像

plt.show()

import pandas as pd import matplotlib.pyplot as plt

读取数据

data = pd.read_excel('a.xlsx')

获取评分数据

scores = data['评分']

创建画布和子图

fig, ax = plt.subplots(figsize=(10, 5))

画直方图

ax.hist(scores, bins=6, range=(0, 5), alpha=0.8)

设置标题、横轴标签、纵轴标签

ax.set_title('Hotel Scores Distribution') ax.set_xlabel('Scores') ax.set_ylabel('Counts')

显示图像

plt.show()

import pandas as pd import matplotlib.pyplot as plt

读取数据

data = pd.read_excel('a.xlsx')

获取评分和价格数据

scores = data['评分'] prices = data['价格']

创建画布和子图

fig, ax = plt.subplots(figsize=(10, 5))

画散点图

ax.scatter(prices, scores, alpha=0.5)

设置标题、横轴标签、纵轴标签

ax.set_title('Hotel Scores vs Prices') ax.set_xlabel('Prices') ax.set_ylabel('Scores')

显示图像

plt.show()

import pandas as pd import seaborn as sns

读取数据

data = pd.read_excel('a.xlsx')

获取油尖旺地区的评分数据

yau_tsim_mong_scores = data.loc[data['地区'] == '油尖旺']['评分']

创建画布和子图

fig, ax = plt.subplots(figsize=(10, 5))

画箱线图

sns.boxplot(yau_tsim_mong_scores, ax=ax)

设置标题、横轴标签

ax.set_title('Scores Distribution in Yau Tsim Mong Region') ax.set_xlabel('Scores')

显示图像

plt.show()