Lambda with multiple arguments

Question

Below is an extract of a dataframe containing stock information with multiple tickers:

      ticker       date    open    high     low   close      volume        rsi
0        A2M 2015-03-31   0.555   0.595   0.530   0.565   4816294.0        NaN
1        A2M 2015-04-30   0.475   0.500   0.475   0.500    531816.0        NaN
2        A2M 2015-05-29   0.475   0.475   0.455   0.465   5665854.0        NaN
3        A2M 2015-06-30   0.640   0.650   0.630   0.640   1691918.0  63.636364
4        A2M 2015-07-31   0.750   0.760   0.730   0.735    714927.0  76.047904
64672    ZFX 2008-01-31  10.090  10.490   9.860  10.280   4484500.0        NaN
64673    ZFX 2008-02-29  10.650  11.130  10.650  11.130  15525073.0        NaN
64674    ZFX 2008-03-31  10.010  10.080   9.920   9.980   4256951.0        NaN
64675    ZFX 2008-04-30   9.900  10.190   9.850  10.100   3522569.0  21.238157
64676    ZFX 2008-05-30   9.750   9.750   9.450   9.500   8270995.0  16.253845

I require the addition of indicators from the ta-lib package, with the indicators to be grouped by ticker. I successfully implemented the RSI using the following code:

monthly_raw_data['rsi'] = monthly_raw_data.groupby('ticker')['close'].apply(lambda x: ta.RSI(x, timeperiod=3))

However, when trying to implement CCI, it has multiple arguments and I don't know how to implement through a lambda expression. I've tried the below:

monthly_raw_data['cci'] = monthly_raw_data.groupby('ticker')['close'].apply(lambda x: ta.CCI(monthly_raw_data['high'], monthly_raw_data['low'], x, timeperiod=12))

I get the following error message:

 Exception: input array lengths are different

I have also tried separating into a different function:

def cci(df):
    cci = ta.CCI(monthly_raw_data['high'], monthly_raw_data['low'], monthly_raw_data['close'], timeperiod=6)
    return cci

monthly_raw_data['cci'] = monthly_raw_data.groupby('ticker').apply(lambda df: cci(df))

However, I receive the following error message:

 TypeError: incompatible index of inserted column with frame index

When I create a separate dataframe to see what is happening it seems to be changing the dataframe to the below:

    0   1   2   3   4   5   6   7   8   9   ... 64667   64668   64669   64670   64671   64672   64673   64674   64675   64676
ticker                                                                                  
A2M NaN NaN NaN NaN NaN 41.584158   28.0    82.316119   199.492386  172.390572  ... -39.470637  -0.791007   -90.955414  -147.191601 -130.347794 -124.040219 -72.940833  -79.655329  -62.732749  -83.135392
AAN NaN NaN NaN NaN NaN 41.584158   28.0    82.316119   199.492386  172.390572  ... -39.470637  -0.791007   -90.955414  -147.191601 -130.347794 -124.040219 -72.940833  -79.655329  -62.732749  -83.135392
AAP NaN NaN NaN NaN NaN 41.584158   28.0    82.316119   199.492386  172.390572  ... -39.470637  -0.791007   -90.955414  -147.191601 -130.347794 -124.040219 -72.940833  -79.655329  -62.732749  -83.135392
ABB NaN NaN NaN NaN NaN 41.584158   28.0    82.316119   199.492386  172.390572  ... -39.470637  -0.791007   -90.955414  -147.191601 -130.347794 -124.040219 -72.940833  -79.655329  -62.732749  -83.135392
ABC NaN NaN NaN NaN NaN 41.584158   28.0    82.316119   199.492386  172.390572  ... -39.470637  -0.791007   -90.955414  -147.191601 -130.347794 -124.040219 -72.940833  -79.655329  -62.732749  -83.1353

Any help would be greatly appreciated.

Does any of the answers at https://stackoverflow.com/questions/19914937/applying-function-with-multiple-arguments-to-create-a-new-pandas-column helps you ? — Marcel Flygare, May 22 '20 at 09:02
I've tried to use the x['high'], x.['low'] etc. but get TypeError: incompatible index of inserted column with frame index. When i try to input axis argument - it returns an error of unexpected keyword. — daveskis, May 22 '20 at 09:18

Lambda with multiple arguments

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