条形图
import pandas as pd
reviews = pd.read_csv('fandango_scores.csv') # 电影评分的数据集，包含了电影名称和不同对象的评分
cols = ['FILM','RT_user_norm','Metacritic_user_nom','IMDB_norm','Fandango_Ratingvalue','Fandango_Stars']
norm_reviews = reviews[cols]
print(norm_reviews[:1])
FILM RT_user_norm Metacritic_user_nom \
0 Avengers: Age of Ultron (2015) 4.3 3.55
IMDB_norm Fandango_Ratingvalue Fandango_Stars
0 3.9 4.5 5.0
import matplotlib.pyplot as plt
from numpy import arange
num_cols = ['RT_user_norm','Metacritic_user_nom','IMDB_norm','Fandango_Ratingvalue','Fandango_Stars']
bar_height = reviews[cols].loc[0,num_cols].values # 拿到值，y轴高度
print(bar_height)
bar_positions = arange(5)+0.75 # x轴位置
print(bar_positions)
fig, ax = plt.subplots()
ax.bar(bar_positions,bar_height,0.3)
plt.show()
[4.3 3.55 3.9 4.5 5.0]
[0.75 1.75 2.75 3.75 4.75]
# 从数据集中选取两组对象的评分数据
import matplotlib.pyplot as plt
from numpy import arange
num_cols = ['RT_user_norm','Metacritic_user_nom','IMDB_norm','Fandango_Ratingvalue','Fandango_Stars']
bar_height = reviews[cols].loc[0,num_cols].values # 拿到值，y轴高度
print(bar_height)
bar_positions = arange(5)+0.75 # x轴位置
print(bar_positions)
tick_positions = range(1,6)
fig, ax = plt.subplots()
ax.barh(bar_positions,bar_height,0.3) # 柱子距离，柱子高度，柱子宽度
ax.set_yticks(tick_positions) # 显示刻度值
ax.set_yticklabels(num_cols)
ax.set_ylabel('Rating Source') # 显示标签
ax.set_xlabel('Average Rating')
ax.set_title('Average User Rating For Avengers: Age of Ultron (2015)')
plt.show()
[4.3 3.55 3.9 4.5 5.0]
[0.75 1.75 2.75 3.75 4.75]
散点图
fig, ax = plt.subplots()
ax.scatter(reviews['Fandango_Ratingvalue'] ,reviews['RT_user_norm'] )
ax.set_xlabel('Fandango')
ax.set_ylabel('Rotten Tomatoes')
plt.show()
flg2 = plt.figure(figsize=(10,5)) # 创建画图区间，设置长高度
ax1 = flg2.add_subplot(1,2,1)
ax2 = flg2.add_subplot(1,2,2)
ax1.scatter(reviews['Fandango_Ratingvalue'] ,reviews['RT_user_norm'] )
ax1.set_xlabel('Fandango')
ax1.set_ylabel('Rotten Tomatoes')
ax2.scatter(reviews['RT_user_norm'] ,reviews['Fandango_Ratingvalue'] )
ax2.set_xlabel('Rotten Tomatoes')
ax2.set_ylabel('Fandango')
plt.show()
