Python中的文本数据可视化技巧

import jiebafrom wordcloud import WordCloudimport matplotlib.pyplot as plttext = "Python是一门优秀的编程语言，它具有强大的功能和广泛的应用场景。同时，Python还拥有丰富的第三方库和工具，方便程序员进行开发和调试。"# 使用jieba进行分词words = jieba.cut(text)words_list = ' '.join(words)# 创建词云对象wc = WordCloud(width=800, height=600, background_color='white', font_path='simhei.ttf')# 生成词云图wc.generate(words_list)# 展示词云图plt.imshow(wc, interpolation='bilinear')plt.axis('off')plt.show()

import matplotlib.pyplot as plt# 数据languages = ['Python', 'Java', 'C', 'C++', 'JavaScript']popularity = [22.8, 17.6, 8.8, 7.6, 6.1]# 创建柱状图plt.bar(languages, popularity)# 设置图形标题和坐标轴标签plt.title('Programming Languages and Popularity')plt.xlabel('Programming Languages')plt.ylabel('Popularity')# 显示柱状图plt.show()

import matplotlib.pyplot as plt# 数据x = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]y = [6, 10, 8, 4, 7, 5, 3, 9, 2, 1]# 创建散点图plt.scatter(x, y)# 设置图形标题和坐标轴标签plt.title('Scatter Plot')plt.xlabel('X-axis')plt.ylabel('Y-axis')# 显示散点图plt.show()

import matplotlib.pyplot as pltimport numpy as np# 数据np.random.seed(0)x = np.random.randn(1000)# 创建统计图plt.hist(x, bins=20)# 设置图形标题和坐标轴标签plt.title('Histogram')plt.xlabel('X-axis')plt.ylabel('Frequency')# 显示统计图plt.show()