Utility Function for DataFrames

[mtanco]

Maybe not Real Applications, but a lot of demos will use data frames, so a scoring function that takes a data frame and returns one would be nice. This is a rough draft which needs to be cleaned up, but putting hear as a place holder for the ModelOps Utiliies

def get_predictions(rows: pd.DataFrame):
    # handle nulls
    rows = rows.where(pd.notnull(rows), "")

   # every value needs to be a string
    vals = rows.values.tolist()
    for i in range(len(vals)):
        vals[i] = [str(x) for x in vals[i]]

    # create a string that is in the expected dictionary format
    dictionary = '{"fields": ' + str(df.columns.tolist()) + ', "rows": ' + str(vals) + '}'
    dictionary = dictionary.replace("'", '"'). #mlops needs double quotes!

   # use the utility function
    dict_preds = mlops_get_score('https://model.wave.h2o.ai/f2659e88-cbad-4ae0-baf0-e25daef42461/model/score',
                                 dictionary)

   # turn the returned dict into a dataframe
    preds = pd.DataFrame(data=dict_preds['score'], columns=dict_preds['fields'])

    # join with original data, assumption is the row order never changes
    return pd.concat([rows, preds], axis=1)