Calculating RSI In Python

I am trying to calculate RSI on a dataframe df = pd.DataFrame({'Close': [100,101,102,103,104,105,106,105,103,102,103,104,103,105,106,107,108,106,105,107,109]}) df['Change'] = df['

Solution 1:

(edited)

Here's an implementation of your formula.

RSI_LENGTH = 7

rolling_gain = df["Gain"].rolling(RSI_LENGTH).mean()
df.loc[RSI_LENGTH-1, "RSI"] = rolling_gain[RSI_LENGTH-1]

for inx in range(RSI_LENGTH, len(df)):
    df.loc[inx, "RSI"] = (df.loc[inx-1, "RSI"] * (RSI_LENGTH -1) + df.loc[inx, "Gain"]) / RSI_LENGTH

The result is:

    Close  Change  Gain  Loss  Index       RSI
0     100     NaN   0.0   0.0      0       NaN
1     101     1.0   1.0   0.0      1       NaN
2     102     1.0   1.0   0.0      2       NaN
3     103     1.0   1.0   0.0      3       NaN
4     104     1.0   1.0   0.0      4       NaN
5     105     1.0   1.0   0.0      5       NaN
6     106     1.0   1.0   0.0      6  0.857143
7     105    -1.0   0.0   1.0      7  0.734694
8     103    -2.0   0.0   2.0      8  0.629738
9     102    -1.0   0.0   1.0      9  0.539775
10    103     1.0   1.0   0.0     10  0.605522
11    104     1.0   1.0   0.0     11  0.661876
12    103    -1.0   0.0   1.0     12  0.567322
13    105     2.0   2.0   0.0     13  0.771990
14    106     1.0   1.0   0.0     14  0.804563
15    107     1.0   1.0   0.0     15  0.832483
16    108     1.0   1.0   0.0     16  0.856414
17    106    -2.0   0.0   2.0     17  0.734069
18    105    -1.0   0.0   1.0     18  0.629202
19    107     2.0   2.0   0.0     19  0.825030
20    109     2.0   2.0   0.0     20  0.992883