I am trying to merge buy_prices and sell_prices however it keeps leaving one empty.

buy_prices

     Buy Time   Buy Price
0  2021-01-21  136.869995
1  2021-02-12  135.369995
2  2021-03-24  120.089996
3  2021-04-05  125.900002
4  2021-06-14  130.479996
5  2021-08-12  148.889999
6  2021-10-19  148.759995
7  2022-02-08  174.830002
8  2022-03-25  174.720001
9  2022-06-07  148.710007
10 2022-07-06  142.919998
11 2022-10-25  152.339996
12 2022-11-22  150.179993
13 2023-01-18  135.210007
14 2023-03-15  152.990005
15 2023-08-31  187.869995
16 2023-10-11  179.800003
17 2023-11-09  182.410004

sell_prices

    Sell Time  Sell Price
0  2021-02-11  135.130005
1  2021-02-16  133.190002
2  2021-03-30  119.900002
3  2021-05-05  128.100006
4  2021-08-09  146.089996
5  2021-09-20  142.940002
6  2022-01-13  172.190002
7  2022-02-23  160.070007
8  2022-04-14  165.289993
9  2022-06-14  132.759995
10 2022-08-31  157.220001
11 2022-11-09  134.869995
12 2022-12-07  140.940002
13 2023-03-01  145.309998
14 2023-08-07  178.850006
15 2023-09-18  177.970001
16 2023-10-26  166.889999
17 2023-12-29  192.529999

I run this code and it produces that result.

trades = buy_prices.merge(sell_prices, how='left', left_on=['Buy Time', 'Buy Price'], right_on = ['Sell Time','Sell Price'])

Results

     Buy Time   Buy Price Sell Time  Sell Price
0  2021-01-21  136.869995       NaT         NaN
1  2021-02-12  135.369995       NaT         NaN
2  2021-03-24  120.089996       NaT         NaN
3  2021-04-05  125.900002       NaT         NaN
4  2021-06-14  130.479996       NaT         NaN
5  2021-08-12  148.889999       NaT         NaN
6  2021-10-19  148.759995       NaT         NaN
7  2022-02-08  174.830002       NaT         NaN
8  2022-03-25  174.720001       NaT         NaN
9  2022-06-07  148.710007       NaT         NaN
10 2022-07-06  142.919998       NaT         NaN
11 2022-10-25  152.339996       NaT         NaN
12 2022-11-22  150.179993       NaT         NaN
13 2023-01-18  135.210007       NaT         NaN
14 2023-03-15  152.990005       NaT         NaN
15 2023-08-31  187.869995       NaT         NaN
16 2023-10-11  179.800003       NaT         NaN
17 2023-11-09  182.410004       NaT         NaN

Why do I get NaT and NaN? How can I fix this? I added data types in case. Thanks in advance.

Buy Time     datetime64[ns]
Buy Price           float64
dtype: object
Sell Time     datetime64[ns]
Sell Price           float64
dtype: object