Python: How to calculate the running difference between entry point and point?

Question

Title may be misleading, not sure what this is called what I am aiming to do.

I want to calculate the difference between the first time I buy, at 79, until I sell, at 38, which I then calculate 38 until 34, where a buy happens again.

Please see the desired output for clarification.

Data for reproducibility:

df = pd.DataFrame([[1, 0], [1, 0], [1, 0],[1, 0],[1, 0],[1, 0],[0, 1],[0, 1],[0, 1],[0, 1],[0, 1],[0, 1],[1, 0],[1, 0],[1, 0],[1, 0],[1, 0],[1, 0],[1, 0],[0, 1],[0, 1],[0, 1],[0, 1],[0, 1],[1, 0],[1, 0],[1, 0],[1, 0],[1, 0]], columns=['BUY', 'SELL'])
df['Price'] = np.random.randint(30, 100, df.shape[0])

Current output.

  Price BUY SELL
0   79  1   0
1   47  1   0
2   70  1   0
3   58  1   0
4   53  1   0
5   57  1   0
6   38  0   1
7   86  0   1
8   64  0   1
9   53  0   1
10  47  0   1
11  30  0   1
12  34  1   0
13  96  1   0
14  79  1   0
15  81  1   0
16  31  1   0
17  76  1   0
18  38  1   0
19  38  0   1
20  61  0   1
21  50  0   1
22  85  0   1
23  55  0   1
24  80  1   0
25  31  1   0
26  82  1   0
27  44  1   0
28  53  1   0

Desired output.

Price  BUY SELL Buy_price Difference    
0   79  1   0   79   0
1   47  1   0   79  -0.4050632911
2   70  1   0   79  -0.1139240506
3   58  1   0   79  -0.2658227848
4   53  1   0   79  -0.3291139241
5   57  1   0   79  -0.2784810127
6   38  0   1   38  0
7   86  0   1   38  1.263157895
8   64  0   1   38  0.6842105263
9   53  0   1   38  0.3947368421
10  47  0   1   38  0.2368421053
11  30  0   1   38  -0.2105263158
12  34  1   0   34  0
13  96  1   0   34  1.823529412
14  79  1   0   34  1.323529412
15  81  1   0   34  1.382352941
16  31  1   0   34  -0.08823529412
17  76  1   0   34  1.235294118
18  38  1   0   34  0.1176470588
19  38  0   1   38  0
20  61  0   1   38  0.6052631579
21  50  0   1   38  0.3157894737
22  85  0   1   38  1.236842105
23  55  0   1   38  0.4473684211
24  80  1   0   80  0
25  31  1   0   80  -0.6125
26  82  1   0   80  0.025
27  44  1   0   80  -0.45
28  53  1   0   80  -0.3375

In row 1, difference is -0.4. How is it calculated? or do you just want the buy_price column? — Rishin Rahim
– Rishin Rahim, Commented Apr 30, 2021 at 8:09

Rishin Rahim · Accepted Answer · 2021-04-30 08:36:01Z

1

There may be more efficient ways to do this. but the below snippet will give the desired result as well:

price = df.Price.values
buy = df.BUY.values
sell = df.SELL.values
difference = [0]
buy_price = [price[0]]
for i,v in enumerate(price[1:]):
    if sell[i+1] == buy[i]:
        buy_price.append(v)
    else:
        buy_price.append(buy_price[-1])
    difference.append((buy_price[-1] - v)/buy_price[-1])
        
    
df['buy_price'] =  buy_price
df['difference'] =  difference
df

Output:

    BUY SELL    Price   buy_price   difference
0   1   0   75  75  0.000000
1   1   0   30  75  0.600000
2   1   0   98  75  -0.306667
3   1   0   34  75  0.546667
4   1   0   62  75  0.173333
5   1   0   95  75  -0.266667
6   0   1   88  88  0.000000
7   0   1   61  88  0.306818
8   0   1   98  88  -0.113636
9   0   1   69  88  0.215909
10  0   1   53  88  0.397727
11  0   1   66  88  0.250000
12  1   0   79  79  0.000000
13  1   0   72  79  0.088608
14  1   0   67  79  0.151899
15  1   0   66  79  0.164557
16  1   0   56  79  0.291139
17  1   0   34  79  0.569620
18  1   0   97  79  -0.227848
19  0   1   72  72  0.000000
20  0   1   96  72  -0.333333
21  0   1   65  72  0.097222
22  0   1   39  72  0.458333
23  0   1   78  72  -0.083333
24  1   0   86  86  0.000000
25  1   0   70  86  0.186047
26  1   0   72  86  0.162791
27  1   0   85  86  0.011628
28  1   0   92  86  -0.069767

answered Apr 30, 2021 at 8:36

Rishin Rahim

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1 Comment

doomdaam Over a year ago

I will give it a try when I'm back in the pc!

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