[英]Row-wise union of dataframe in pandas
Say that I have two DataFrames
's: 假设我有两个
DataFrames
:
df1 = pd.DataFrame([('A', 0.3), ('B', 0.4)], columns = ('ID', 'Buy'))
df2 = pd.DataFrame([('B', 3), ('A', 4)], columns = ('ID', 'Sell'))
That yield: 产量:
ID Buy
0 A 0.3
1 B 0.4
and 和
ID Sell
0 B 3
1 A 4
respectively. 分别。
Now, I want to obtain a single DataFrame
that collects the data, namely: 现在,我想获得一个收集数据的
DataFrame
,即:
ID Buy Sell
0 A 0.3 4
1 B 0.4 3
Note that the order of the lines in df1
and df2
may not be the same. 请注意,
df1
和df2
中的行顺序可能不同。 Furthermore, there might ID's that appear only in one frame and not in the other --- in this case the missing value should be filled with NaN
I guess. 此外,可能会有ID仅出现在一个帧中而不出现在另一帧中-在这种情况下,我猜想缺失的值应该用
NaN
填充。
How can I do it? 我该怎么做?
I tried something like 我尝试了类似的东西
pd.concat([df1, df2], join = 'outer', axis = 1)
but doesn't return the desired result. 但不会返回期望的结果。
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.