Adding a new column in one DataFrame where values are based from a second DataFrame

I have two DataFrames, df_a is the DataFrame we want to manipulate. I want to add a new column but the values are found in a second DataFrame with a similar column name.

Let me expound.

df_a contains

_ | Code | Speed | Velocity |
0 |  DA  |   23  |    22    |
1 |  ES  |   23  |    22    |
2 |  DA  |   23  |    22    |
3 |  GA  |   23  |    22    |
4 |  NU  |   23  |    22    |

df_b contains

_ | Code |     Name    |
0 |  DA  |   DinoAero  |
1 |  ES  |    Espeed   |
2 |  GA  |    GeoArk   |
3 |  NU  |  NewUnicorn |

I want to merge or concatenate these two DataFrames that the result should look like this:

_ | Code |     Name     | Speed | Velocity |
0 |  DA  |   DinoAero   |   23  |    22    |
1 |  ES  |    Espeed    |   23  |    22    |
2 |  DA  |   DinoAero   |   23  |    22    |
3 |  GA  |    GeoArk    |   23  |    22    |
4 |  NU  |  NewUnicorn  |   23  |    22    | 

I’m quite new to both Python and Pandas, I am having a hard time also how to search the proper question for this so I’ve decided to ask in stackoverflow and risk my downvote just for me to learn. Appreciate the patience for everyone willing to share wisdom.

>Solution :

You just want to pd.merge() (which is similar to a SQL join).

In your case:

new_df = pd.merge(df_a,df_b,how='left',on='Code')
new_df = new_df[['Code','Name','Speed','Velocity']] # if you want to re-arrange the columns in your order