# Buggy code
def generate_text_table_sell_reason(data: Dict[str, Dict], results: DataFrame) -> str:
    """
    Generate small table outlining Backtest results
    :param data: Dict of <pair: dataframe> containing data that was used during backtesting.
    :param results: Dataframe containing the backtest results
    :return: pretty printed table with tabulate as string
    """
    tabular_data = []
    headers = ["Sell Reason", "Count", "Profit", "Loss", "Profit %"]
    for reason, count in results["sell_reason"].value_counts().iteritems():
        result = results.loc[results["sell_reason"] == reason]
        profit = len(result[result["profit_abs"] >= 0])
        loss = len(result[result["profit_abs"] < 0])
        profit_mean = round(result["profit_percent"].mean() * 100.0, 2)
        tabular_data.append([reason.value, count, profit, loss, profit_mean])
    return tabulate(tabular_data, headers=headers, tablefmt="pipe")


# Traceback (Exception)
2020-02-20 22:47:28,025 - freqtrade - ERROR - Fatal exception!
Traceback (most recent call last):
File "/opt/tradebot/freqtrade/.env/lib/python3.7/site-packages/talib/__init__.py", line 20, in wrapper
for arg in chain(args, kwargs.values())
StopIteration

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/freqtrade/freqtrade/main.py", line 36, in main
return_code = args['func'](args)
File "/freqtrade/freqtrade/commands/optimize_commands.py", line 76, in start_hyperopt
hyperopt.start()
File "/freqtrade/freqtrade/optimize/hyperopt.py", line 488, in start
preprocessed = self.backtesting.strategy.tickerdata_to_dataframe(data)
File "/freqtrade/freqtrade/strategy/interface.py", line 448, in tickerdata_to_dataframe
for pair, pair_data in tickerdata.items()}
File "/freqtrade/freqtrade/strategy/interface.py", line 448, in <dictcomp>
for pair, pair_data in tickerdata.items()}
File "/freqtrade/freqtrade/strategy/interface.py", line 464, in advise_indicators
return self.populate_indicators(dataframe, metadata)
File "/freqtrade/user_data/strategies/MyDev.py", line 205, in populate_indicators
dataframe['mfi'] = ta.MFI(dataframe)
File "talib/_abstract.pxi", line 352, in talib._ta_lib.Function.__call__
File "talib/_abstract.pxi", line 383, in talib._ta_lib.Function.__call_function
File "/opt/tradebot/freqtrade/.env/lib/python3.7/site-packages/talib/__init__.py", line 24, in wrapper
return func(*args, **kwargs)
File "talib/_func.pxi", line 8454, in talib._ta_lib.MFI
Exception: volume is not double

# Fixed code
def generate_text_table_sell_reason(
    data: Dict[str, Dict], stake_currency: str, max_open_trades: int, results: DataFrame
) -> str:
    """
    Generate small table outlining Backtest results
    :param data: Dict of <pair: dataframe> containing data that was used during backtesting.
    :param results: Dataframe containing the backtest results
    :return: pretty printed table with tabulate as string
    """
    tabular_data = []
    headers = [
        "Sell Reason",
        "Sells",
        "Wins",
        "Draws",
        "Losses",
        "Avg Profit %",
        "Cum Profit %",
        f"Tot Profit {stake_currency}",
        "Tot Profit %",
    ]
    for reason, count in results["sell_reason"].value_counts().iteritems():
        result = results.loc[results["sell_reason"] == reason]
        wins = len(result[result["profit_abs"] > 0])
        draws = len(result[result["profit_abs"] == 0])
        loss = len(result[result["profit_abs"] < 0])
        profit_mean = round(result["profit_percent"].mean() * 100.0, 2)
        profit_sum = round(result["profit_percent"].sum() * 100.0, 2)
        profit_tot = result["profit_abs"].sum()
        profit_percent_tot = round(
            result["profit_percent"].sum() * 100.0 / max_open_trades, 2
        )
        tabular_data.append(
            [
                reason.value,
                count,
                wins,
                draws,
                loss,
                profit_mean,
                profit_sum,
                profit_tot,
                profit_percent_tot,
            ]
        )
    return tabulate(tabular_data, headers=headers, tablefmt="pipe")