Small Dataset Output

#output from small data set (that still works)

def _convert_pandas_statistics(stat):
        content_dict = {}
        percentiles = []
        if "25%" in stat:
            percentiles = [0] * 100
            percentiles[24] = stat["25%"]
            percentiles[49] = stat["50%"]
            percentiles[74] = stat["75%"]
        if "mean" in stat:
            content_dict["mean"] = stat["mean"]
        if "mean" in stat and "count" in stat:
            content_dict["sum"] = stat["mean"] * stat["count"]
        if "max" in stat:
            content_dict["maximum"] = stat["max"]
        if "std" in stat:
            content_dict["stdDev"] = stat["std"]
        if "min" in stat:
            content_dict["minimum"] = stat["min"]
        if percentiles:
            content_dict["approxPercentiles"] = percentiles
        return content_dict

df = fv.get_batch_data()
stats = df.describe()
final_stats = []
for col in stats.columns:
    stat = _convert_pandas_statistics(stats[col].to_dict())
    stat["dataType"] = (
                "Fractional"
                if isinstance(stats[col].dtype, type(np.dtype(np.float64)))
                else "Integral"
            )
    stat["isDataTypeInferred"] = "false"
    stat["column"] = col.split(".")[-1]
    stat["completeness"] = 1
    final_stats.append(stat)
final_stats

VersionWarning: No training dataset version was provided to initialise batch scoring . Defaulting to version 1.
2023-05-02 07:26:41,928 INFO: USE `workshop_featurestore`
2023-05-02 07:26:42,454 INFO: SELECT `fg0`.`close_0` `close_0`, `fg0`.`ema_0` `ema_0`, `fg0`.`high_0` `high_0`, `fg0`.`low_0` `low_0`, `fg0`.`open_0` `open_0`, `fg0`.`rsi_0` `rsi_0`, `fg0`.`sma_0` `sma_0`, `fg0`.`volume_0` `volume_0`, `fg0`.`close_1` `close_1`, `fg0`.`ema_1` `ema_1`, `fg0`.`high_1` `high_1`, `fg0`.`low_1` `low_1`, `fg0`.`open_1` `open_1`, `fg0`.`rsi_1` `rsi_1`, `fg0`.`sma_1` `sma_1`, `fg0`.`volume_1` `volume_1`, `fg0`.`close_2` `close_2`, `fg0`.`ema_2` `ema_2`, `fg0`.`high_2` `high_2`, `fg0`.`low_2` `low_2`, `fg0`.`open_2` `open_2`, `fg0`.`rsi_2` `rsi_2`, `fg0`.`sma_2` `sma_2`, `fg0`.`volume_2` `volume_2`, `fg0`.`close_3` `close_3`, `fg0`.`ema_3` `ema_3`, `fg0`.`high_3` `high_3`, `fg0`.`low_3` `low_3`, `fg0`.`open_3` `open_3`, `fg0`.`rsi_3` `rsi_3`, `fg0`.`sma_3` `sma_3`, `fg0`.`volume_3` `volume_3`
FROM `workshop_featurestore`.`historical_data_1` `fg0`
UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.

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