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The equivalent Java code for the Pandas operation index_df = pd.concat(data_frames).groupby(level=0).mean() requires combining multiple Map<Date, OHLCV> objects and then averaging the OHLCV values for each date.

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import org.knowm.xchange.dto.marketdata.OHLCV;
import org.knowm.xchange.service.marketdata.MarketDataService;
import org.knowm.xchange.Exchange;
import org.knowm.xchange.ExchangeFactory;
import org.knowm.xchange.currency.CurrencyPair;
import org.knowm.xchange.binance.BinanceExchange;

import java.util.*;
import java.util.stream.Collectors;

public class PriceWeightedIndexCalculator {

    public static void main(String[] args) {
        String exchangeId = "binance";
        List<String> tokens = Arrays.asList("ETH", "ADA", "BNB", "SOL", "AVAX", "TRX");
        calculatePriceWeightedIndex(tokens, exchangeId);
    }

    public static void calculatePriceWeightedIndex(List<String> tokens, String exchangeId) {
        try {
            Exchange exchange = ExchangeFactory.INSTANCE.createExchange(BinanceExchange.class);
            MarketDataService marketDataService = exchange.getMarketDataService();
            List<Map<Date, OHLCV>> dataFrames = new ArrayList<>();

            for (String token : tokens) {
                try {
                    List<OHLCV> ohlcvList = marketDataService.getHistoricalOHLCV(new CurrencyPair(token + "/USDT"), org.knowm.xchange.utils.Interval.ONE_DAY, null);
                    Map<Date, OHLCV> ohlcvMap = ohlcvList.stream().collect(Collectors.toMap(OHLCV::getTimestamp, ohlcv -> ohlcv));
                    dataFrames.add(ohlcvMap);
                } catch (Exception e) {
                    System.out.println("Failed to fetch data for " + token + ": " + e.getMessage());
                }
            }

            if (!dataFrames.isEmpty()) {
                Map<Date, List<OHLCV>> groupedData = new HashMap<>();

                for (Map<Date, OHLCV> dataFrame : dataFrames) {
                    for (Map.Entry<Date, OHLCV> entry : dataFrame.entrySet()) {
                        groupedData.computeIfAbsent(entry.getKey(), k -> new ArrayList<>()).add(entry.getValue());
                    }
                }

                Map<Date, OHLCV> averageData = groupedData.entrySet().stream()
                        .collect(Collectors.toMap(
                                Map.Entry::getKey,
                                entry -> calculateAverageOHLCV(entry.getValue())
                        ));

                // Now you can use averageData for further processing or plotting
                System.out.println("Calculated Price Weighted Index:");
                averageData.forEach((date, ohlcv) -> System.out.println(date + " -> " + ohlcv));
            } else {
                System.out.println("No data fetched for tokens");
            }
        } catch (Exception e) {
            e.printStackTrace();
        }
    }

    private static OHLCV calculateAverageOHLCV(List<OHLCV> ohlcvList) {
        double open = ohlcvList.stream().mapToDouble(ohlcv -> ohlcv.getOpen().doubleValue()).average().orElse(0);
        double high = ohlcvList.stream().mapToDouble(ohlcv -> ohlcv.getHigh().doubleValue()).average().orElse(0);
        double low = ohlcvList.stream().mapToDouble(ohlcv -> ohlcv.getLow().doubleValue()).average().orElse(0);
        double close = ohlcvList.stream().mapToDouble(ohlcv -> ohlcv.getClose().doubleValue()).average().orElse(0);
        double volume = ohlcvList.stream().mapToDouble(ohlcv -> ohlcv.getVolume().doubleValue()).average().orElse(0);

        return new OHLCV(null, open, high, low, close, volume);
    }
}