pandas 将表/数据帧与 Python 中的公共列连接起来
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Joining Table/DataFrames with common Column in Python
提问by Rahul Bhatia
I have two DataFrames:
我有两个数据帧：
df1 = ['Date_Time',
'Temp_1',
'Latitude',
'N_S',
'Longitude',
'E_W']
df2 = ['Date_Time',
'Year',
'Month',
'Day',
'Hour',
'Minute',
'Seconds']
As You can see both DataFrames have Date_Timeas a common column. I want to Join these two DataFrames by matching Date_Time.
正如您所看到的，两个 DataFrame 都有Date_Time一个公共列。我想通过匹配Date_Time.
My current code is: df.join(df2, on='Date_Time'), but this is giving an error.
我当前的代码是：df.join(df2, on='Date_Time')，但这是一个错误。
回答by Andy Hayden
You are looking for a merge:
您正在寻找一个merge：
df1.merge(df2, on='Date_Time')
The keywords are the same as for join, but joinuses only the index, see "Database-style DataFrame joining/merging".
关键字与 for 相同join，但join仅使用索引，请参阅“数据库样式的 DataFrame 加入/合并”。
Here's a simple example:
这是一个简单的例子：
import pandas as pd
df1 = pd.DataFrame([[1, 2, 3]])
df2 = pd.DataFrame([[1, 7, 8],[4, 9, 9]], columns=[0, 3, 4])
In [4]: df1
Out[4]:
0 1 2
0 1 2 3
In [5]: df2
Out[5]:
0 3 4
0 1 7 8
1 4 9 9
In [6]: df1.merge(df2, on=0)
Out[6]:
0 1 2 3 4
0 1 2 3 7 8
In [7]: df1.merge(df2, on=0, how='outer')
Out[7]:
0 1 2 3 4
0 1 2 3 7 8
1 4 NaN NaN 9 9
If you try and join on a column you get an error:
如果您尝试加入列，则会出现错误：
In [8]: df1.join(df2, on=0)
# error!
Exception: columns overlap: array([0], dtype=int64)
See "Joining key columns on an index".
请参阅“连接索引上的键列”。
