01
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效果
(上图·基于github网页自助动态排行功能截图)
(上图·基于下方code制作)
02
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code
# https://blog.csdn.net/weixin_42512684/article/details/104286367
# 导入库函数
import random
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import matplotlib.animation as animation
from IPython.display import HTML
import matplotlib
#防止动漫内存太大,报错
matplotlib.rcParams['animation.embed_limit'] = 2**128
# 控制中文显示https://blog.csdn.net/weixin_44301621/article/details/103531398
plt.rcParams['font.sans-serif']=['SimHei']
plt.rcParams['axes.unicode_minus']=False
#pandas读取数据,且去列名分别为name,group,year和value的值;
#url = 'https://gist.githubusercontent.com/johnburnmurdoch/4199dbe55095c3e13de8d5b2e5e5307a/raw/fa018b25c24b7b5f47fd0568937ff6c04e384786/city_populations'
#df = pd.read_csv(url, usecols=['name', 'group', 'year', 'value'])
#df.head()
df = pd.read_csv(r'C:\Users\ysl\Desktop\shengnianvalue.csv',encoding='gbk',usecols=[ 'name', 'group','year', 'value'])
#导入random函数,randomcolor用于生成颜色代码
# randomcolor生成颜色代码原理,
# 【1-9/A-F】15个数字随机组合成6位字符串前面再加上一个“#”号键
import random
def randomcolor():
colorlist = ['1','2','3','4','5','6','7','8','9','A','B','C','D','E','F']
color =''
for i in range(6):
color += random.choice(colorlist)
return '#'+ color
# 对地区列表进行去重,分类;
area_list1 = set(df['name'])
# color_list用于存放随机生成颜色代码个数
# 因为后面区域个数 要与颜色个数保持一致,这里用了len函数;
color_list = []
for i in range(len(area_list1)):
str_1 = randomcolor()
color_list.append(str_1)
str_1 = randomcolor()
# area_list转化为列表
area_list_1 = [i for i in area_list1]
print(color_list)
print(area_list_1)
#colors表示 所在城市:颜色 一一对应字典形式;
colors =dict(zip(area_list_1,color_list))
print(colors)
#group_lk为 城市:所在区域 --对应字典形式;
group_lk = df.set_index('name')['group'].to_dict()
print(group_lk)
# 用plt加理图表,figsize表示图标长宽,ax表示标签
fig, ax = plt.subplots(figsize=(16, 9))
# dras_barchart生成current_year这一年各城市人口基本情况;
def draw_barchart(current_year):
# dff对year==current_year的行,以value从升序方式排序,取后十名也就是最大值;
dff = df[df['year'].eq(current_year)].sort_values(by='value', ascending=True).tail(15)
# 所有坐标、标签清除
ax.clear()
# 显示颜色、城市名字
ax.barh(dff['name'], dff['value'], color=[colors[x] for x in dff['name']])
dx = dff['value'].max() / 200
# ax.text(x,y,name,font,va,ha)
# x,y表示位置;
# name表示显示文本;
# va,ba分别表示水平位置,垂直放置位置;
for i, (value, name) in enumerate(zip(dff['value'], dff['name'])):
# ax.text(value - dx, i, name, size=14, weight=600, ha='right', va='center')
ax.text(value + dx, i, name, size=14, weight=600, ha='left', va='center')
# ax.text(value - dx, i - .25, group_lk[name], size=10, color='#444444', ha='right', va='baseline')
# ax.text(value + dx, i, f'{value:,.0f}', size=14, ha='left', va='center')
ax.text(value - dx, i, f'{value:,.0f}', size=12, ha='right', va='center')
# ax.transAxes表示轴坐标系,(1,0.4)表示放置位置
ax.text(1, 0.4, current_year, transform=ax.transAxes, color='#777777', size=46, ha='right', weight=800)
ax.text(0, 1.06, '国内生产总值·GDP(亿元)', transform=ax.transAxes, size=12, color='#777777')
# set_major_formatter表示刻度尺格式;
ax.xaxis.set_major_formatter(ticker.StrMethodFormatter('{x:,.0f}'))
ax.xaxis.set_ticks_position('top')
ax.tick_params(axis='x', colors='#777777', labelsize=12)
ax.set_yticks([])
# margins表示自动缩放余额;
ax.margins(0, 0.01)
# 设置后面的网格
ax.grid(which='major', axis='x', linestyle='-')
# 刻度线和网格线是在图标上方还是下方,True为下方
ax.set_axisbelow(True)
# ax.text(0.5, 1.15, '2000-2019年各省市区国内生产总值(前15)', transform=ax.transAxes, size=16, weight=600, ha='center', va='top')
ax.text(1, 0, '数据来源:国家统计局', transform=ax.transAxes, color='#777777', ha='right', bbox=dict(facecolor='white', alpha=0.8, edgecolor='white'))
# 取消图表周围的方框显示
plt.box(False)
# 绘制2018年各城市人口情况
# draw_barchart(2019)
# fig, ax = plt.subplots(figsize=(15, 30))
with plt.xkcd():
fig, ax = plt.subplots(figsize=(15, 8))
draw_barchart(2019)
#将原来的静态图拼接成动画
fig, ax = plt.subplots(figsize=(16, 9))
animator = animation.FuncAnimation(fig, draw_barchart, frames=range(2000, 2019))
#保存到jshtml
HTML(animator.to_jshtml())
#生成video,并保存至指定文件夹中
import os
ffmpegpath = os.path.abspath(r"D:\ffmpeg\bin\ffmpeg.exe")
matplotlib.rcParams["animation.ffmpeg_path"] = ffmpegpath
fig, ax = plt.subplots(figsize=(16, 9))
animator = animation.FuncAnimation(fig, draw_barchart, frames=range(2000, 2020))
writer = animation.FFMpegWriter(fps=1)
animator.save('E:/country_populations1.mp4',writer=writer)
03
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Github网页自助动态排行榜
github地址:https://github.com/FabDevGit/barchartrace
网页自助动态排行榜:https://fabdevgit.github.io/barchartrace/