how continue the loop with the next loop item if the current item produced an error?-CodePudding

I have a function that calculates the RSI indicator from OHLC values stored in a pandas datafram. The function is as follows:

def rsi_indicator(df):
    diff = df.close.diff().values
    gains = diff
    losses = -diff
    with np.errstate(invalid='ignore'):
        gains[(gains < 0) | np.isnan(gains)] = 0.0
        losses[(losses <= 0) | np.isnan(losses)] = 1e-10  # we don't want divide by zero/NaN
    n = 14
    m = (n - 1) / n
    ni = 1 / n
    try:
        g = gains[n] = np.nanmean(gains[:n])
        l = losses[n] = np.nanmean(losses[:n])
    except IndexError as e:
         ????
    gains[:n] = losses[:n] = np.nan
    for i, v in enumerate(gains[n:], n):
        g = gains[i] = ni * v   m * g
    for i, v in enumerate(losses[n:], n):
        l = losses[i] = ni * v   m * l
    rs = gains / losses
    rsi = 100 - (100 / (1   rs))
    return rsi

I am looping through few dataframes to calculate the RSI but whenever I have a dataframe with no enough records to calculate the indicator values I get an IndexError:

IndexError: index 14 is out of bounds for axis 0 with size 13

How can I continue using the next item in the loop list when I get such an error?

I added some ???? where I need the code to fix this issue, otherwise feel free to change the code however you like.

CodePudding user response：

It is generally a bad practice to suppress errors or exceptions without handling them, but this can be easily done like this:

    # block raising an exception
except:
    pass # doing nothing on exception```
This can obviously be used in any other control statement, such as a loop:

for i in xrange(0,960):
    try:
        ... run your code
    except:
        pass