Pandas拼接时报错'Length of values does not match length of index'排查

核心问题原因 #

1. 全局列表未重置：所有存储K线字段的列表（如StartedAt、Low等）定义在循环外部，每次迭代币种时不会清空，导致后续迭代中列表包含之前所有币种的数据，创建dataframe时长度远超当前币种的K线条数，触发"Length of values does not match length of index"错误。
2. 字段映射错误：代码中错误地将Low列表赋值给open列，Open列表赋值给low列，导致K线数据字段对应错误。

修复方案 #

• 将所有K线数据列表移至循环内部，每次处理新币种前重置为空。
• 修正字段映射关系，确保open/close/high/low对应正确的列表。
• 优化DataFrame创建逻辑，直接通过字典批量生成，避免逐列赋值的冗余操作。

修改后的完整代码 #

import dydx3 as dy
import pandas as pd
import os

dir = os.getcwd()

client = dy.Client(
    host='https://api.dydx.exchange'
)

markets_1m = {
    'BTC-USD': f'{dir}\\markets\\BTC-USD_1MIN.csv', 
    'ETH-USD': f'{dir}\\markets\\ETH-USD_1MIN.csv', 
    'LINK-USD': f'{dir}\\markets\\LINK-USD_1MIN.csv',
    'SOL-USD': f'{dir}\\markets\\SOL-USD_1MIN.csv',
    'ATOM-USD': f'{dir}\\markets\\ATOM-USD_1MIN.csv',
    'XMR-USD': f'{dir}\\markets\\XMR-USD_1MIN.csv',
    'RUNE-USD': f'{dir}\\markets\\RUNE-USD_1MIN.csv',
}

def get_price_data_1m():
    try:
        for ticker, path in markets_1m.items():
            # 每次迭代重置数据列表
            StartedAt = []
            UpdatedAt = []
            Market = []
            Resolution = []
            Low = []
            High = []
            Open = []
            Close = []
            BaseTokenVolume = []
            Trades = []
            UsdVolume = []
            StartingOpenInterest = []

            candles = client.public.get_candles(
                market=ticker,
                resolution='1MIN',
            )
            for i in candles.data['candles']:
                StartedAt.append(i['startedAt'])
                UpdatedAt.append(i['updatedAt'])
                Market.append(i['market'])
                Resolution.append(i['resolution'])
                Low.append(i['low'])
                High.append(i['high'])
                Open.append(i['open'])
                Close.append(i['close'])
                BaseTokenVolume.append(i['baseTokenVolume'])
                Trades.append(i['trades'])
                UsdVolume.append(i['usdVolume'])
                StartingOpenInterest.append(i['startingOpenInterest'])

            # 直接用字典创建DataFrame，修正字段映射
            dataframe = pd.DataFrame({
                'startedAt': StartedAt,
                'updatedAt': UpdatedAt,
                'market': Market,
                'resolution': Resolution,
                'open': Open,
                'high': High,
                'low': Low,
                'close': Close,
                'baseTokenVolume': BaseTokenVolume,
                'trades': Trades,
                'usdVolume': UsdVolume,
                'startingOpenInterest': StartingOpenInterest
            })

            price_history = pd.read_csv(path)
            # 拼接数据并去重排序
            combined = pd.concat([price_history, dataframe], join='outer', ignore_index=True)
            combined.drop_duplicates(subset=['startedAt'], keep='first', inplace=True)
            combined.sort_values(by=['startedAt'], inplace=True)
            
            combined.to_csv(f'{dir}\\markets\\{ticker}_1MIN.csv', index=False)
            print(f"完成 {ticker} 数据更新")

    except Exception as e:
        print(f'错误: {e}')

# 调用函数
get_price_data_1m()

额外优化点 #

• 路径拼接使用双反斜杠\\替代单反斜杠，避免转义字符问题，也可以用os.path.join()进一步增强兼容性：

  path = os.path.join(dir, 'markets', f'{ticker}_1MIN.csv')
  

• 移除了不必要的reset_index(drop=True)，因为ignore_index=True已经会重置拼接后的索引。

内容的提问来源于stack exchange，提问作者ProjectJords