我有df1:
x y no.
0 -17.7 -0.785430 y1
1 -15.0 -3820.085000 y4
2 -12.5 2.138833 y3
.. .... ........ ..
40 15.6 5.486901 y2
41 19.2 1.980686 y3
42 19.6 9.364718 y2
和df2:
delta y x
0 0.053884 -17.7
1 0.085000 -15.0
2 0.143237 -12.5
.. ........ ....
40 0.113099 15.6
41 0.102245 19.2
42 0.235282 19.6
它们都有43行，并且x列在两者上完全相同。
当我在x上合并它们时，我得到了一个123行的df:
x y no. delta y
0 -17.7 -0.785430 y1 0.053884
1 -15.0 -3820.085000 y4 0.085000
2 -12.5 2.138833 y3 0.143237
3 -12.4 1.721205 y3 0.251180
4 -12.1 2.227343 y2 0.127343
.. ... ... .. ...
118 12.1 1.642526 y3 0.143886
119 14.4 2576.435000 y4 0.171000
120 15.6 5.486901 y2 0.113099
121 19.2 1.980686 y3 0.102245
122 19.6 9.364718 y2 0.235282
输入:final = df1.merge(df2, on="x")x float64y float64不。对象dtype:对象
δ y float64x float64dtype:对象
x float64y float64不。对象dtype:对象
δ y float64x float64dtype:对象
x float64y float64不。对象dtype:对象
δ y float64x float64dtype:对象
df1 = pd。DataFrame({"x":{0:-17.7,1:-15.0,2:-12.5,3:-12.4,4:-12.1,5:-11.2,6:-8.9,7:-7.5,8:-7.5,9:-6.0,10:-6.0,11:-4.7,12:-4.1,13:-3.8,14:-3.4,15:-3.4,16:-1.9,17:-1.5,18:-1.1,19:-0.4,20:-0.1,21:3.5,22日:3.8,23日:5.3,24:5.3,25日:5.3,26日:5.3,27日:5.3,28日:5.3,29日:5.3,30日:5.3,31日:5.3,32:6.4,33:6.8,34:6.8,35:10.2,36:10.3,37:11.9,38:12.1,39:14.4,40:15.6,41:19.2,42:19.6},"y":{0:-0.7854295,1:-3820.085,2:2.1388333,3:1.7212046,4:2.227343、5:0.04315967、6:-0.9616607、7:-1.9878536、8:-0.52237016、9:-283.27216、10:-282.5332、11:-0.4335017、12:-1.1585577、13:-0.008831219、14:848.92303、15:-57.407845、16:-9.010686、17:-3.2473037、18:0.5536767、19:1.8351307、20:4.8347697、21:-6.45842、22:- 0.9338831、25:97.65833、26:1.6500127、27:1.6500127、28:97.65833、29:97.65833、30:1.65500127、31:1.9058462、34:227.5592、35:857.7455、36:-0.68584794、37:1.6785516, 38: 1.6425261, 39: 2576.435, 40: 5.4869013, 41: 1.9806856, 42: 9.364718}，":{0:"日元",1:"y4",2:y3, 3: y3, 4: y2, 5: y3, 6: y2, 7: y2, 8: y2, 9:"y4",10:"y4",11:"日元",12:y3, 13:"日元",14:"y4",15:"y4",16:y4, 17: y4, 18:"日元",19:y3, 20: y4, 21: y2, 22: y3, 23: y3, 24: y3, 25日:"y4",26日:y3, 27日:y3, 28日:"y4",29日:y3, 30日:‘y4’,31日:"y4",32:y2, 33: y3, 34: y3, 35:"y4",36:y3, 37: y3, 38: y3, 39: y4, 40: y2, 41: y3, 42:‘y2}})
df2 = pd。DataFrame({'delta y': {0: 0.05388353000000001, 1: 0.08500000000003638, 2: 0.1432367999999999994, 3: 0.251179999999999999996, 4: 0.12734299999999976, 5: 0.36285006000000003, 6: 0.13833930000000005, 7: 0.512141464, 8: 1.9776299999884, 9: 0.272159999999999853, 10: 0.4667999999999779, 11: 0.2692114, 12: 0.00890970000000002, 13: 0.314458351, 14: 906.34703, 15: 0.016154999999999999777, 16: 0.3723036999999998, 18: 0.2988478, 19: 0.006991300000000145, 20: 0.14423030000000026, 21:0.0415799999999999973, 22: 0.013554200000000183, 23: 0.174865600000000183, 23: 0.1748652000000000007, 24: 0.17486560000000007, 25: 0.038669999999999999621, 26: 0.541264, 27: 0.541264, 28: 0.0386699999999999621, 29: 96.5495813, 30: 96.0469873, 31: 0.0386699999999999621, 32: 0.05542200000000008, 33: 0.1670513, 34: 225.82040510000002, 35: 0.38250000000005, 36: 0.9580486, 37: 0.10641100000000002, 38: 0.14388610000000002, 39: 0.17099999999999992174, 40: 0.113098699999999999999922, 41: 0.1022448999999999999977}， 'x': {0};-17.7, 1: -15.0, 2: -12.5, 3: -12.4, 4: -12.1, 5: -11.2, 6: -8.9, 7: -7.5, 8: -7.5, 9: -6.0, 10: -6.0, 11: -4.7, 12: -4.1, 13: -3.8, 14: -3.4, 15: -3.4, 16: -1.9, 17: -1.5, 18: -1.1, 19: -0.4, 20: -0.1, 21: 3.5, 22日:3.8,23日:5.3,24:5.3,25日:5.3,26日:5.3,27日:5.3,28日:5.3,29日:5.3,30日:5.3,31日:5.3,32:6.4,33:6.8,34:6.8,35:10.2,36:10.3,37:11.9,38:12.1,39:14.4,40:15.6,41:19.2,42:19.6}})
final = df1.merge(df2, on="x")
问题是x值不是唯一的，因此合并重复行以获得所有组合。在一个简单的例子中
>>> import pandas as pd
>>> df1=pd.DataFrame({"a":[1,2,3,2], "b":['a', 'b', 'c', 'd']})
>>> df2=pd.DataFrame({"a":[1,2,3,2], "c":['aa', 'bb', 'cc', 'dd']})
>>> df1.merge(df2, on='a')
a b c
0 1 a aa
1 2 b bb
2 2 b dd
3 2 d bb
4 2 d dd
5 3 c cc
2在列中不是唯一的，并且得到所有的组合(注意b——>d和d——>dd)。
在您的示例中，x列在两个数据框架中是相同的。这也意味着索引没有改变，您可以将您想要的列分配给df1。
df1["delta y"] = df2["delta y"]
尝试如下:df1.join(df2)
join是一个列向左连接
pd。Merge是按列的内部连接
pd。Concat是逐行外连接
pd.concat:接受Iterable参数。因此，它不能直接接受dataframe(使用[df,df2])DataFrame的尺寸应该沿着轴
匹配Join and pd.merge:可以接受DataFrame参数
ref:合并两个数据帧
尝试以下语法，我建议您仔细阅读python的官方文档，链接在底部。我认为df1和df2中的x值可能不同它们不是100%相同的。这可能是由于小数的原因。
import pandas as pd
left = pd.DataFrame(
{
"key": ["K0", "K1", "K2", "K3"],
"A": ["A0", "A1", "A2", "A3"],
"B": ["B0", "B1", "B2", "B3"],
}
)
right = pd.DataFrame(
{
"key": ["K0", "K1", "K2", "K3"],
"C": ["C0", "C1", "C2", "C3"],
"D": ["D0", "D1", "D2", "D3"],
}
)
result = pd.merge(left, right, on="key")
结果图像Python合并，连接，连接官方指南