我有两个数据框
current_bin.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 16 entries, 0 to 15
Data columns (total 3 columns):
id 16 non-null object
fpd 16 non-null float64
avgSpeedBinID 16 non-null object
dtypes: float64(1), object(2)
current_bin 数据框如下所示:
current_bin
id fpd avgSpeedBinID
0 1.1.4.1 2.818623 1
1 1.1.4.10 0.266681 10
2 1.1.4.11 0.250017 11
3 1.1.4.12 0.234749 12
4 1.1.4.13 0.222515 13
5 1.1.4.14 0.216150 14
6 1.1.4.15 0.218368 15
7 1.1.4.16 0.227663 16
8 1.1.4.2 1.475454 2
9 1.1.4.3 0.805842 3
10 1.1.4.4 0.581797 4
11 1.1.4.5 0.450314 5
12 1.1.4.6 0.379107 6
13 1.1.4.7 0.335155 7
14 1.1.4.8 0.305992 8
15 1.1.4.9 0.284210 9
和
avg.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 16 entries, 0 to 15
Data columns (total 4 columns):
avgSpeedBinID 16 non-null int64
avgBinSpeed 16 non-null float64
avgSpeedBinDesc 16 non-null object
temp 16 non-null int64
dtypes: float64(1), int64(2), object(1)
看起来像:
avgSpeedBinID avgBinSpeed avgSpeedBinDesc temp
0 1 3 speed < 2.5mph 0
1 2 5 2.5mph <= speed < 7.5mph 0
2 3 10 7.5mph <= speed < 12.5mph 0
3 4 15 12.5mph <= speed < 17.5mph 0
4 5 20 17.5mph <= speed <22.5mph 0
5 6 25 22.5mph <= speed < 27.5mph 0
6 7 30 27.5mph <= speed < 32.5mph 0
7 8 35 32.5mph <= speed < 37.5mph 0
8 9 40 37.5mph <= speed < 42.5mph 0
9 10 45 42.5mph <= speed < 47.5mph 0
10 11 50 47.5mph <= speed < 52.5mph 0
11 12 55 52.5mph <= speed < 57.5mph 0
12 13 60 57.5mph <= speed < 62.5mph 0
13 14 65 62.5mph <= speed < 67.5mph 0
14 15 70 67.5mph <= speed < 72.5mph 0
15 16 75 72.5mph <= speed 0
两个数据帧在 avgSpeedBinID 字段上的值为 1 到 16，但是，当我尝试将数据帧合并在一起时
avg.merge(current_bin, on='avgSpeedBinID')
我得到一个空数据框
avgSpeedBinID avgBinSpeed avgSpeedBinDesc temp id fpd
为什么会发生这种情况，我该如何解决这个问题？
最佳答案
当前 bin 数据帧中的 avgSpeedBinID 是 str 类型，avg 中是 int。
只需将 str 转换为 int 即可进行合并。
current_bin['avgSpeedBinID'] = current_bin['avgSpeedBinID'].astype(int)
avg.merge(current_bin, on='avgSpeedBinID')
avgSpeedBinID avgBinSpeed avgSpeedBinDesc temp id fpd
0 1 3 speed < 2.5mph 0 1.1.4.1 2.818623
1 2 5 2.5mph <= speed < 7.5mph 0 1.1.4.2 1.475454
2 3 10 7.5mph <= speed < 12.5mph 0 1.1.4.3 0.805842
3 4 15 12.5mph <= speed < 17.5mph 0 1.1.4.4 0.581797
4 5 20 17.5mph <= speed <22.5mph 0 1.1.4.5 0.450314
5 6 25 22.5mph <= speed < 27.5mph 0 1.1.4.6 0.379107
6 7 30 27.5mph <= speed < 32.5mph 0 1.1.4.7 0.335155
7 8 35 32.5mph <= speed < 37.5mph 0 1.1.4.8 0.305992
8 9 40 37.5mph <= speed < 42.5mph 0 1.1.4.9 0.284210
9 10 45 42.5mph <= speed < 47.5mph 0 1.1.4.10 0.266681
10 11 50 47.5mph <= speed < 52.5mph 0 1.1.4.11 0.250017
11 12 55 52.5mph <= speed < 57.5mph 0 1.1.4.12 0.234749
12 13 60 57.5mph <= speed < 62.5mph 0 1.1.4.13 0.222515
13 14 65 62.5mph <= speed < 67.5mph 0 1.1.4.14 0.216150
14 15 70 67.5mph <= speed < 72.5mph 0 1.1.4.15 0.218368
15 16 75 72.5mph <= speed 0 1.1.4.16 0.22763
关于python - Pandas 合并返回空数据框，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/25792086/