Apply function to all df rows using value from row

I have a dataframe column consisting of timestamps which I need to pass to a function as an argument to retrieve a price for that given timestamp. Then create a new "price" column in the dataframe.

The df looks like this:

             date_time   timestamp
0  2022-09-20 23:55:02  1663718102
1  2022-09-21 23:55:02  1663804502
2  2022-09-22 23:59:02  1663891142
3  2022-09-23 23:59:02  1663977542
4  2022-09-24 23:59:02  1664063942
5  2022-09-25 23:59:03  1664150343
6  2022-09-26 23:59:02  1664236742
7  2022-09-27 23:59:03  1664323143
8  2022-09-28 23:59:03  1664409543
9  2022-09-29 23:59:03  1664495943
10 2022-09-30 23:59:02  1664582342
11 2022-10-01 23:59:02  1664668742
12 2022-10-02 23:59:02  1664755142
13 2022-10-03 23:59:03  1664841543

Currently I can pass any one of these timestamps to the function individually but am unsure how to combine the function and the dataframe to produce the third column.

def fetch_price(timestamp):
data = session_auth.query_kline(
    symbol="BTCUSDT",
    interval=1,
    limit=2,
    from_time=timestamp)
price = data["result"][0]["close"]
return price

>Solution :

You can do

df["new_column"] = df.timestamp.apply(fetch_price)

This applies the function to every row/timestamp of your DataFrame and creates a new column "new_column"