pandas merge df

import pandas as pd
df1 = pd.DataFrame({'lkey': ['foo', 'bar', 'baz', 'foo'],
                    'value': [1, 2, 3, 5]})
df2 = pd.DataFrame({'rkey': ['foo', 'bar', 'baz', 'foo'],
                    'value': [5, 6, 7, 8]})
df1.merge(df2, left_on='lkey', right_on='rkey')

Here is what the above code is Doing:
1. The merge function takes two parameters: the first is the dataframe to be merged into the second.
2. The left_on and right_on parameters specify the columns to be used for the merge.
3. The result of the merge is a new dataframe that contains all of the columns from both of the input dataframes.
4. The merge function automatically detects that the lkey and rkey columns are the same and uses them as the key for the merge.
5. The merge function also automatically detects that the value columns are the same and uses them as the values for the merge.
6. The result of the merge is a new dataframe that contains all of the columns from both of the input dataframes.
7. The merge function automatically detects that the lkey and rkey columns are the same and uses them as the key for the merge.
8. The merge function also automatically detects that the value columns are the same and uses them as the values for the merge.
9. The result of the merge is a new dataframe that contains all of the columns from both of the input dataframes, including the lkey and rkey columns.
10. The lkey and rkey columns are the keys for the merge, so the order of the rows in the result is the same as the order of the rows in the lkey column of the first dataframe.
11. The value column is the values for the merge, so the values in the result are the sum of the values in the value columns of the two dataframes.