I have two DataFrames:
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_Time as a common column. I want to Join these two DataFrames by matching Date_Time.
My current code is: df.join(df2, on='Date_Time'), but this is giving an error.
You are looking for a merge:
df1.merge(df2, on='Date_Time')
The keywords are the same as for join, but join uses only the index, see "Database-style DataFrame joining/merging".
Here's a simple example:
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:
In [8]: df1.join(df2, on=0)
# error!
Exception: columns overlap: array([0], dtype=int64)
See "Joining key columns on an index".
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With