如何基于相同的日期时间 x 轴在时间绘制两个不同的数据框列

Question

您好，我有一个这样的数据框：

        Date  Influenza[it]  Febbre[it]  Cefalea[it]  Paracetamolo[it]  \
0    2008-01            989        2395         1291              2933   
1    2008-02            962        2553         1360              2547   
2    2008-03           1029        2309         1401              2735   
3    2008-04           1031        2399         1137              2296    

     Unnamed: 6 tot_incidence  
0           NaN          4.56  
1           NaN          5.98  
2           NaN          6.54  
3           NaN          6.95  

我想用 x 轴上的 Date 列和 y 轴上的 Influenza[it] 列和另一列像 Febbre[it] 绘制不同的数字。然后再次x轴Date列，y轴Influenza[it]列和另一列（例如Paracetamolo[it]）等等。我试图弄清楚是否有一种快速的方法可以在不完全操纵数据帧的情况下实现它。

Answer 1

您可以简单地绘制 3 个不同的子图。

import pandas as pd
import matplotlib.pyplot as plt

dic = {"Date" : ["2008-01","2008-02", "2008-03", "2008-04"],
       "Influenza[it]" : [989,962,1029,1031],
        "Febbre[it]" : [2395,2553,2309,2399],
        "Cefalea[it]" : [1291,1360,1401,1137],
        "Paracetamolo[it]" : [2933,2547,2735,2296]}

df = pd.DataFrame(dic)
#optionally convert to datetime
df['Date'] = pd.to_datetime(df['Date'])

fig, ax = plt.subplots(1,3, figsize=(13,7))
df.plot(x="Date", y=["Influenza[it]","Febbre[it]" ], ax=ax[0])
df.plot(x="Date", y=["Influenza[it]","Cefalea[it]" ], ax=ax[1])
df.plot(x="Date", y=["Influenza[it]","Paracetamolo[it]" ], ax=ax[2])

#optionally equalize yaxis limits
for a in ax:
    a.set_ylim([800, 3000])

plt.show()

---

如果您想在 jupyter 笔记本中分别绘制每个图，则以下内容可能会满足您的需求。
此外，我们将日期从格式 year-week 转换为日期时间，以便能够使用 matplotlib 绘制它们。

%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt

dic = {"Date" : ["2008-01","2008-02", "2008-03", "2008-04"],
       "Influenza[it]" : [989,962,1029,1031],
        "Febbre[it]" : [2395,2553,2309,2399],
        "Cefalea[it]" : [1291,1360,1401,1137],
        "Paracetamolo[it]" : [2933,2547,2735,2296]}

df = pd.DataFrame(dic)
#convert to datetime, format year-week -> date (monday of that week)
df['Date'] = [ date + "-1" for date in df['Date']] # add "-1" indicating monday of that week
df['Date'] = pd.to_datetime(df['Date'], format="%Y-%W-%w")

cols = ["Febbre[it]", "Cefalea[it]", "Paracetamolo[it]"]
for col in cols:
    plt.close()
    fig, ax = plt.subplots(1,1)
    ax.set_ylim([800, 3000])
    ax.plot(df.Date, df["Influenza[it]"], label="Influenza[it]")
    ax.plot(df.Date, df[col], label=col)
    ax.legend()
    plt.show()