使用数据地址：链接：/s/1wXtZRDcM-JKk_dIDRyd_dg?pwd=pyth
提取码：pyth
（电影评分数据）
导入数据
import pandas as pdimport matplotlib.pyplot as pltreviews = pd.read_csv('fandango_scores.csv')cols = ['FILM', 'RT_user_norm', 'Metacritic_user_nom', 'IMDB_norm', 'Fandango_Ratingvalue']norm_reviews = reviews[cols]print(norm_reviews[:5])'''FILM RT_user_norm Metacritic_user_nom \0 Avengers: Age of Ultron () 4.3 3.55 1Cinderella () 4.0 3.75 2 Ant-Man () 4.5 4.05 3Do You Believe? () 4.2 2.35 4 Hot Tub Time Machine 2 () 1.4 1.70 IMDB_norm Fandango_Ratingvalue 0 3.90 4.5 1 3.55 4.5 2 3.90 4.5 3 2.70 4.5 4 2.55 3.0 '''fandango_distribution = norm_reviews['Fandango_Ratingvalue'].value_counts()fandango_distribution = fandango_distribution.sort_index()imdb_distribution = norm_reviews['IMDB_norm'].value_counts()imdb_distribution = imdb_distribution.sort_index()print(fandango_distribution)'''2.722.822.953.043.133.253.343.493.593.683.793.853.9 124.074.1 164.2 124.3 114.474.594.644.83Name: Fandango_Ratingvalue, dtype: int64'''print(imdb_distribution)'''2.0012.1012.1512..3022.4522.5012.5512.6022.7042.7552.8022.8512.9012.9533.0023.0543.1013.1593.2063.2543.3093.3573.4013.4573.5043.5573.60 103.6553.7083.7563.8033.8543.9093.9524.0014.0514.1044.1514.2024.301Name: IMDB_norm, dtype: int64'''
绘制柱状图，注意柱状图不同于条状图，区别在于：一个柱子高度，表示所取到的跨度（bin）中的所有值的个数。
fig = plt.figure(figsize=(5,20))ax1 = fig.add_subplot(4,1,1)ax2 = fig.add_subplot(4,1,2)ax3 = fig.add_subplot(4,1,3)ax4 = fig.add_subplot(4,1,4)ax1.hist(norm_reviews['Fandango_Ratingvalue'], bins=20, range=(0, 5))ax1.set_title('Distribution of Fandango Ratings')ax1.set_ylim(0, 50)ax2.hist(norm_reviews['RT_user_norm'], 20, range=(0, 5))ax2.set_title('Distribution of Rotten Tomatoes Ratings')ax2.set_ylim(0, 50)ax3.hist(norm_reviews['Metacritic_user_nom'], 20, range=(0, 5))ax3.set_title('Distribution of Metacritic Ratings')ax3.set_ylim(0, 50)ax4.hist(norm_reviews['IMDB_norm'], 20, range=(0, 5))ax4.set_title('Distribution of IMDB Ratings')ax4.set_ylim(0, 50)plt.show()
箱线图的画法
num_cols = ['RT_user_norm', 'Metacritic_user_nom', 'IMDB_norm', 'Fandango_Ratingvalue']fig, ax = plt.subplots()ax.boxplot(norm_reviews[num_cols].values)ax.set_xticklabels(num_cols, rotation=45)ax.set_ylim(0,5)plt.show()
