Pandas 按列合并数据帧

我有两个数据帧：

df1 = pd.DataFrame({'dateRep': ['2020-09-10', '2020-08-10', '2020-07-10', 
                              '2020-24-03', '2020-23-03', '2020-22-03'],
                    'cases': [271, 321, 137, 
                              8, 0, 1],
                    'countriesAndTerritories': ['Kenya', 'Kenya','Kenya',
                                               'Uganda', 'Uganda', 'Uganda']})
df1

及

我希望按日期将其合并到一个数据帧中：

df3 = pd.DataFrame({'date': ['2020-15-02', '2020-16-02', '2020-17-02',
                             '2020-22-03', '2020-23-03', '2020-24-03',
                             '2020-06-10', '2020-07-10', '2020-07-10', '2020-08-10', '2020-08-10', '2020-09-10'],
                    'cases': [2.0, 0.0, 5.0, 
                              1.0, 0.0, 8.0, 
                              0.0, -5.0, 137, -3.7, 321, 271],
                    'country_refion': ['Kenya', 'Kenya','Kenya',
                                       'Uganda', 'Uganda', 'Uganda',
                                       'Uganda', 'Uganda', 'Kenya', 'Uganda', 'Kenya', 'Kenya']})
df3

---

我尝试了.join（）和.concatenate（）方法，但没有按预期工作。提前感谢您的帮助

您可以使用

df.append

和

df.combine\u first（）

：

---

哇，太快了。多谢各位！你的回答很直观。

df3 = pd.DataFrame({'date': ['2020-15-02', '2020-16-02', '2020-17-02',
                             '2020-22-03', '2020-23-03', '2020-24-03',
                             '2020-06-10', '2020-07-10', '2020-07-10', '2020-08-10', '2020-08-10', '2020-09-10'],
                    'cases': [2.0, 0.0, 5.0, 
                              1.0, 0.0, 8.0, 
                              0.0, -5.0, 137, -3.7, 321, 271],
                    'country_refion': ['Kenya', 'Kenya','Kenya',
                                       'Uganda', 'Uganda', 'Uganda',
                                       'Uganda', 'Uganda', 'Kenya', 'Uganda', 'Kenya', 'Kenya']})
df3

In [297]: x = df1.append(df2)
In [299]: x.date = x.dateRep.combine_first(x.date)
In [301]: x.country_refion = x.country_refion.combine_first(x.countriesAndTerritories)

In [308]: x = x.sort_values('date').drop(['dateRep', 'countriesAndTerritories'], axis=1).reset_index(drop=True)

In [310]: x
Out[310]: 
    cases        date country_refion
0     0.0  2020-06-10         Uganda
1   137.0  2020-07-10          Kenya
2    -5.0  2020-07-10         Uganda
3   321.0  2020-08-10          Kenya
4    -3.7  2020-08-10         Uganda
5   271.0  2020-09-10          Kenya
6     2.0  2020-15-02          Kenya
7     0.0  2020-16-02          Kenya
8     5.0  2020-17-02          Kenya
9     1.0  2020-22-03         Uganda
10    0.0  2020-23-03         Uganda
11    8.0  2020-24-03         Uganda