/
covid19-plot-miyagi-daily.py
executable file
·97 lines (90 loc) · 4.02 KB
/
covid19-plot-miyagi-daily.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
import numpy as np
import pandas as pd
import datetime as dt
from itertools import product
from matplotlib import pyplot as plt
import japanize_matplotlib
from matplotlib import dates as mdates
df_url = "https://raw.githubusercontent.com/nagae/CoVid-19/main/data/CoVid19-Miyagi-daily_patients_by_age.csv"
df = pd.read_csv(df_url, header=[0,1], index_col=0)
df = df.set_index(pd.to_datetime(df.index))
latest_date = df.index[0]
latest_date_str = latest_date.strftime("%Y-%m-%d")
ages = ["10歳未満", "10代", "20代", "30代", "40代", "50代", "60代", "70代", "80代", "90歳以上"]
age_label = ["10-", "10代", "20代", "30代", "40代", "50代", "60代", "70代", "80代", "90+"]
########################################
fig, ax = plt.subplots(2,1,figsize=(18,12*2))
# 最初のグラフ
colors1 = []
for i in range(10):
colors1 += ['C{}'.format(i)]*3
plot_df = df.T.loc[product(ages, ["入院中", "入院調整中", "療養中"])].fillna(0).astype(int).T[-1::-1]
plot_df = plot_df.resample('D').mean()
plot_df['Date'] = plot_df.index.strftime('%y-%m-%d')
plot_df.plot(x='Date', kind='bar', stacked='True', ax=ax[0], color=colors1)
weeks = mdates.WeekdayLocator(byweekday=mdates.SU, tz=None)
ax[0].xaxis.set_major_locator(weeks)
ax[0].set_title("宮城県-年代別患者数 (各年代について，色の薄い順に療養中，入院調整中,入院中)")
ax[0].grid(axis='y', zorder=1)
alphas = [1.0,0.75,0.5]
for pid,p in enumerate(ax[0].patches):
p.set_alpha( alphas[ pid//len(plot_df) % 3])
h,l = ax[0].get_legend_handles_labels()
ax[0].legend(h[::3],age_label,loc="upper left")
# 2つめのグラフ
colors2 = []
for i in range(10):
colors2 += ['C{}'.format(i)]
plot_df = df.T.loc[product(ages, ["入院中"])].fillna(0).astype(int).T[-1::-1]
plot_df = plot_df.resample('D').mean()
plot_df['Date'] = plot_df.index.strftime('%y-%m-%d')
plot_df.plot(x='Date', kind='bar', stacked='True', ax=ax[1], color=colors2)
weeks = mdates.WeekdayLocator(byweekday=mdates.SU, tz=None)
ax[1].xaxis.set_major_locator(weeks)
ax[1].set_title("宮城県-年代別入院者数")
ax[1].grid(axis='y', zorder=1)
h,l = ax[1].get_legend_handles_labels()
ax[1].legend(h,age_label,loc="upper left")
# グラフの保存
plt.savefig("fig/CoVid19-Miyagi-patients_by_age.png", bbox_inches="tight")
########################################
fig, ax = plt.subplots(2,1,figsize=(18,12*2))
# 最初のグラフ
colors1 = []
for i in range(10):
colors1 += ['C{}'.format(i)]*3
colors2 = []
for i in range(10):
colors2 += ['C{}'.format(i)]
# 3つめのグラフ
plot_df = df.T.loc[product(ages, ["入院中", "入院調整中", "療養中"])].fillna(0).astype(int).T[-1::-1]
plot_df = plot_df.apply(lambda x: x/x.sum(), axis=1)
plot_df = plot_df.resample('D').mean()
plot_df['Date'] = plot_df.index.strftime('%y-%m-%d')
plot_df.plot(x='Date', kind="bar",stacked="True",ax=ax[0],color=colors1)
ax[0].set_title("宮城県-患者の年代別比率 (各年代について，色の薄い順に療養中，入院調整中,入院中)")
ax[0].grid(axis='y', zorder=1)
alphas = [1.0,0.75,0.5]
for pid,p in enumerate(ax[0].patches):
p.set_alpha( alphas[ pid//len(plot_df) % 3])
h,l = ax[0].get_legend_handles_labels()
ax[0].legend(h[::3],age_label,loc="center left")
weeks = mdates.WeekdayLocator(byweekday=mdates.SU, tz=None)
ax[0].xaxis.set_major_locator(weeks)
ax[0].set_ylim((0,1))
# 4つめのグラフ
plot_df = df.T.loc[product(ages, ["入院中"])].fillna(0).astype(int).T[-1::-1]
plot_df = plot_df.apply(lambda x: x/x.sum(), axis=1)
plot_df = plot_df.resample('D').mean()
plot_df['Date'] = plot_df.index.strftime('%y-%m-%d')
plot_df.plot(x='Date', kind="bar",stacked="True",ax=ax[1],color=colors2)
ax[1].set_title("宮城県-入院者の年代別比率")
ax[1].grid(axis='y', zorder=1)
h,l = ax[1].get_legend_handles_labels()
ax[1].legend(h, age_label, loc="center left")
weeks = mdates.WeekdayLocator(byweekday=mdates.SU, tz=None)
ax[1].xaxis.set_major_locator(weeks)
ax[1].set_ylim((0,1))
# グラフの保存
plt.savefig("fig/CoVid19-Miyagi-patients_by_age_rate.png", bbox_inches="tight")
plt.show()