data_analysis27

笔记

import matplotlib.pyplot as plt

import pandas as pd
import numpy as np

file_path = './pandas_data/IMDB-Movie-Data.csv'

df = pd.read_csv(file_path)

# 统计分类的列表
temp_list = df["Genre"].str.split(",").tolist() # [[],[],[]]

genre_list = list(set([i for j in temp_list for i in j]))

# 构造全为0的数组
zeros_df = pd.DataFrame(np.zeros((df.shape[0],len(genre_list))), columns=genre_list)
# print(zeros_df)

# 给每个电影出现分类的位置赋值为1
for i in range(df.shape[0]):
    # zero_df,loc[0,["Sci-fi","Mucical"]] = 1
    zeros_df.loc[i,temp_list[i]] = 1

# print(zeros_df.head(3))

# 统计每个分类的电影的数量和
genre_count = zeros_df.sum(axis=0)
print(genre_count)

# 排序
genre_count = genre_count.sort_values()
_x = genre_count.index
_y = genre_count.values

# 画图
plt.figure(figsize=(20,8),dpi=80)
plt.bar(range(len(_x)),_y)
plt.xticks(range(len(_x)),_x)

plt.show()