如何基于相同的日期时间x轴在时间上绘制两个不同的数据帧列

Question

您好我有这样的数据框：

        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  

我想在x轴上绘制Date列和y轴Influenza[it]列以及另一列Febbre[it]的不同图形。然后再次x轴Date列，y轴Influenza[it]列和另一列（例如Paracetamolo[it]）等等。我试图找出是否有一种快速的方法来制作它而不完全操纵数据帧。

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()

<小时/> 如果您想在jupyter笔记本中单独绘制每个绘图，以下可能会执行您想要的操作 此外，我们将格式year-week的日期转换为日期时间，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()