Reputation: 189
I have two different dataframes, one is date combinations, and one is city pairs:
df_date_combinations:
+-------------------+-------------------+
| fs_date| ss_date|
+-------------------+-------------------+
|2022-06-01T00:00:00|2022-06-02T00:00:00|
|2022-06-01T00:00:00|2022-06-03T00:00:00|
|2022-06-01T00:00:00|2022-06-04T00:00:00|
+-------------------+-------------------+
city pairs:
+---------+--------------+---------+--------------+
|fs_origin|fs_destination|ss_origin|ss_destination|
+---------+--------------+---------+--------------+
| TLV| NYC| NYC| TLV|
| TLV| ROM| ROM| TLV|
| TLV| BER| BER| TLV|
+---------+--------------+---------+--------------+
I want to combine them so I will have the following dataframe:
+----------+----------+---------+--------------+---------+--------------+
| fs_date| ss_date|fs_origin|fs_destination|ss_origin|ss_destination|
+----------+----------+---------+--------------+---------+--------------+
|2022-06-01|2022-06-02| TLV| NYC| NYC| TLV|
|2022-06-01|2022-06-03| TLV| NYC| NYC| TLV|
|2022-06-01|2022-06-04| TLV| NYC| NYC| TLV|
|2022-06-01|2022-06-02| TLV| ROM| ROM| TLV|
|2022-06-01|2022-06-03| TLV| ROM| ROM| TLV|
|2022-06-01|2022-06-04| TLV| ROM| ROM| TLV|
|2022-06-01|2022-06-02| TLV| BER| BER| TLV|
|2022-06-01|2022-06-03| TLV| BER| BER| TLV|
|2022-06-01|2022-06-04| TLV| BER| BER| TLV|
+----------+----------+---------+--------------+---------+--------------+
Thanks!
Upvotes: 0
Views: 170
Reputation: 61
Pandas actually has built-in methods to do this, we use concat
to concatenate the dataframes. You can read how to do this here:
The part that is pertinent to you would be:
pd.concat([df_date_combinations, city_pairs], axis = 1)
Hope this helps!
Upvotes: 0