Encountering ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()

Question

I have a function

def cruise_fun(speed, accl, acmx, dcmx):
    count = 0
    index = []
    for i in range(len(speed.dropna())):
        if ((speed[i]>40) & (accl[i]<acmx*0.2) & (accl[i]>dcmx*0.2)):
            count +=1
            index.append(i)
                    
    return count, index

This function is being called in the following statement

cruise_t_all, index_all =cruise_fun(all_data_speed[0], acc_val_all[0], acc_max_all, decc_max_all)

all_data_speed and acc_val_all are two dataframes of 1 column and 38287 rows. acc_max_all and decc_max_all are two float64 values. I have tried to implement solutions provided in stackoverflow as much as I could. I have used both and and &. I can not get around the problem.

Answer 1

You are using pandas in the wrong way. You should not loop over all the rows like you do. You can concatenate the columns provided and then check the conditions:

def cruise_fun(speed, accl, acmx, dcmx):
    df = pd.concat([speed.dropna(), accl], axis=1)
    df.columns = ["speed", "accl"]
    mask = (df["speed"] > 40) & df["accl"].between(dcmx * .2, acmx * .2, inclusive=False)
    return mask.sum(), df[mask].index

NB: A few assumptions that I make:

• I assume that you do not have conflicts for your column names, otherwise the concat will not work and you will need to rename your columns first
• I assume that the index from speed.dropna() and accl match but I would not be surprised if it is not the case. You should make sure that this is fine, or better: store everything in the same dataframe