【资料视觉化】COVID新冠疫苗施打一览 Seaborn

今晚来点轻松的。资料视觉化，复习一下DataFrame、seaborn
引用资料来源：country_vaccination.csv Kaggle Dataset
该资料集记录各国施打COVID疫苗的逐日报表，是从Our World in Data网站收集整理出来的。说明：
Data is collected daily from Our World in Data GitHub repository for covid-19, merged and uploaded. Country level vaccination data is gathered and assembled in one single file. Then, this data file is merged with locations data file to include vaccination sources information.

Step 1. 载入资料集：使用pandas DataFrame
本文内相关的栏位是country、total_vaccinations、daily_vaccinations。
Step 2. 依国家别分群、找出国家别是”Taiwan”者( 202笔，资料日截至2021-10-09)
Step 3. 统计 daily_vaccinations 的min max mean median
Step 4. barplpot 画每日接种人数 seaborn
Step 5. lineplot 画累计人数逐日图
成果图：

Source code

# vaccine_sn02.py
import numpy as np 
import pandas as pd 
import seaborn as sn
from matplotlib import rcParams
from matplotlib.ticker import MultipleLocator
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker


''' 以dataframe 读取csv '''
print('以dataframe 读取 csv')
df = pd.read_csv('country_vaccinations.csv')
# 依国家别分群
df = df.groupby('country')
# 找出国家别是”Taiwan”者 (资料日截至2021-10-09)
dfT = df.get_group('Taiwan')
print(f'符合的记录数目: {dfT.count}')
# 只取四栏位
dfTwn = dfT[['country','date','total_vaccinations','daily_vaccinations']]
print(dfTwn.head())
# 统计 daily_vaccinations 的 min max mean median
stat1 = dfTwn['daily_vaccinations'].aggregate(['min', 'max', 'mean', 'median'])
stat1 = stat1.astype(int)
print(stat1)
# total_vaccinations 累计接种人数之最大值
print(f'total vaccinations: Taiwan\n{int(dfTwn["total_vaccinations"].max())}')

# barplpot 画 每日接种人数 seaborn 
rcParams['figure.figsize'] = 15,8
xmajorLocator = MultipleLocator(15)
ax = sn.barplot(x=dfTwn['date'],y=dfTwn['daily_vaccinations'],data= dfTwn)
ax.set_xticklabels(ax.get_xticklabels(),rotation = 45,size=12)
ax.xaxis.set_major_locator(xmajorLocator)
ax.set_title('Daily vaccination ( Taiwan )')
# 存档
plt.savefig('Vaccine_TaiwanDaily.png')
plt.figure()

# lineplot 画 累计人数逐日图
xmajorLocator = MultipleLocator(15)
ax2 = sn.lineplot(data= dfTwn,x=dfTwn['date'],y=dfTwn['total_vaccinations'])
plt.xticks(rotation=45,size=12)
ax2.xaxis.set_major_locator(xmajorLocator)
ax2.set_title('Total vaccination ( Taiwan )')
plt.savefig('Vaccine_TaiwanTotal.png')