Python制作疫情地图

详细讲解视频地址——详细视频讲解

第二弹 绘制词云

导入所需模块

import openpyxl
from wordcloud import WordCloud

读取excel中的数据

# 读取数据
wb = openpyxl.load_workbook('data.xlsx')
# 获取工作表
ws = wb['国内义擎']
frequency_in = {}
for row in ws.values:
    if row[0] == '省份':
        pass
    else:
        frequency_in[row[0]] = float(row[1])

frequency_out = {}
sheet_name = wb.sheetnames
for each in sheet_name:
    if "洲" in each:
        ws = wb[each]
        for row in ws.values:
            if row[0] == '国家':
                pass
            else:
                frequency_out[row[0]] = float(row[1])

生成词云图片

def generate_pic(frequency,name):
    wordcloud = WordCloud(font_path="C:/Windows/Fonts/SIMLI.TTF",
                          background_color="white",
                          width=1920, height=1080)
    # 根据确诊病例的数目生成词云
    wordcloud.generate_from_frequencies(frequency)
    # 保存词云
    wordcloud.to_file('%s.png'%(name))

拓展：

如何使词云更加密集?

以下参数在上图代码中实例化Wordcloud类时填入!

1. 如果max_words小，长尾不明显，词云中小字就少，很多地方没有词去填补空白，就显示得不密集。--> 增大max_words
2. 如果max_font_size与min_font_size没拉开，低频词(长尾部分)就没有小到足够在高频词的空白中填入，字中空白就让整个云显得不密集。--> 增大最大和最小字体之间的差值。
3. 最后调整relative_scaling使交叉方向的比例合适，一些词的空白处就能填入一些较短的低频词进一步减少空白。

调用函数

generate_pic(frequency_in,'国内义擎情况词云图')
generate_pic(frequency_out,'世界义擎词云图')

效果展示

全国各省份疫情词云

世界疫情词云

附上完整代码

import openpyxl
from wordcloud import WordCloud
from pyecharts import options as opts
from pyecharts.charts import WordCloud

# 与即时显示图片相关的模块
'''
import matplotlib.pyplot as plt   # 绘制图像的模块
import numpy as np
from PIL import Image
'''

# 读取数据
wb = openpyxl.load_workbook('data.xlsx')
sheet_names = wb.sheetnames

frequency_out = {}
for each in sheet_names:
    if '洲' in each:
        ws = wb[each]
        for row in ws.values:
            if row[1] == "累计确诊":
                pass
            else:
                frequency_out[row[0]] = float(row[1])
    else:
        pass


# 以省份的确诊病例总数代表其出现的频率
frequency_in = {}
ws = wb['国内疫情']
for row in ws.values:
    if row[1] == "累计确诊":
        pass
    else:
        frequency_in[row[0]] = float(row[1])

def generate_pic(frequency,name):
    # 这里可以事先准备一张图片，可以用作背景
    # background_image = np.array(Image.open('pic.jpg'))
    wordcloud = WordCloud(font_path="C:/Windows/Fonts/SIMLI.TTF",
                          background_color = "red",
                          # mask=background_image,
                          width=1920, height=1080
                          )
    # 按照确诊病例数目生成词云
    wordcloud.generate_from_frequencies(frequency)
    wordcloud.to_file('%s.png'%name)

    # 展示图片
    # plt.imshow(wordcloud, interpolation="bilinear")
    # plt.axis("off")
    # plt.show()

# 调用函数
generate_pic(frequency_in,'国内疫情')
generate_pic(frequency_out,'国外疫情')

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详细讲解视频地址——详细视频讲解
第一弹传送门

期待第三弹噢！