解决IndexError: single positional indexer is out-of-bounds并跳过无数据股票

DevOps 小满

2026-8-19

问题

我写了一段Python代码用来获取印度股市历史数据，每天收盘后（大概20:00-21:00）运行。多数时候能正常输出，但经常触发IndexError: single positional indexer is out-of-bounds异常。排查后发现是部分股票的交易所数据没更新，导致程序直接中断，没法输出其他已经更新的股票结果。需要修改代码，实现跳过无数据的股票，正常处理剩下的股票。

原代码如下：

from datetime import date
from datetime import timedelta
from nsepy import get_history
import pandas as pd
import datetime
# import matplotlib.pyplot as mp

end1 = date.today()
start1 = end1 - timedelta(days=365)

stock = [
         'RELIANCE','HDFCBANK','INFY','ICICIBANK','HDFC','TCS','KOTAKBANK','LT','SBIN','HINDUNILVR','AXISBANK','ITC','BAJFINANCE','BHARTIARTL','ASIANPAINT','HCLTECH','MARUTI','TITAN','BAJAJFINSV','TATAMOTORS',
         'TECHM','SUNPHARMA','TATASTEEL','M&M','WIPRO','ULTRACEMCO','POWERGRID','HINDALCO','NTPC','NESTLEIND','GRASIM','ONGC','JSWSTEEL','HDFCLIFE','INDUSINDBK','SBILIFE','DRREDDY','ADANIPORTS','DIVISLAB','CIPLA',
         'BAJAJ-AUTO','TATACONSUM','UPL','BRITANNIA','BPCL','EICHERMOT','HEROMOTOCO','COALINDIA','SHREECEM','IOC','VEDL','ADANIENT', 'APOLLOHOSP', 'TATAPOWER', 'PIDILITIND', 'SRF', 'NAUKRI', 'ICICIGI', 'DABUR',
         'GODREJCP', 'HAVELLS', 'PEL', 'VOLTAS', 'AUBANK', 'LTI', 'CHOLAFIN', 'AMBUJACEM', 'MARICO', 'SRTRANSFIN','GAIL', 'MCDOWELL-N', 'MPHASIS', 'MINDTREE', 'PAGEIND', 'ZEEL', 'BEL', 'TRENT', 'CROMPTON', 'JUBLFOOD',
         'DLF', 'SBICARD', 'SIEMENS', 'BANDHANBNK', 'IRCTC', 'LAURUSLABS', 'PIIND', 'INDIGO', 'INDUSTOWER','ICICIPRULI', 'MOTHERSON', 'AARTIIND', 'FEDERALBNK', 'BANKBARODA', 'PERSISTENT', 'HINDPETRO', 'ACC',
         'AUROPHARMA', 'COLPAL', 'GODREJPROP', 'MFSL', 'LUPIN', 'BIOCON', 'ASHOKLEY', 'BHARATFORG', 'BERGEPAINT','JINDALSTEL', 'ASTRAL', 'IEX', 'NMDC', 'CONCOR', 'INDHOTEL', 'BALKRISIND', 'PETRONET', 'CANBK', 'ALKEM',
         'DIXON', 'DEEPAKNTR', 'DALBHARAT', 'TVSMOTOR', 'ATUL', 'HDFCAMC', 'TATACOMM', 'MUTHOOTFIN', 'TATACHEM','SAIL', 'IDFCFIRSTB', 'PFC', 'BOSCHLTD', 'MRF', 'NAVINFLUOR', 'CUMMINSIND', 'IGL', 'IPCALAB', 'COFORGE',
         'ESCORTS', 'TORNTPHARM', 'LTTS', 'RECLTD', 'LICHSGFIN', 'BATAINDIA', 'HAL', 'PNB', 'GUJGASLTD', 'UBL','3MINDIA','ABB','AIAENG','APLAPOLLO','AARTIDRUGS','AAVAS','ABBOTINDIA','ADANIGREEN','ATGL','ABCAPITAL',
         'ABFRL','ABSLAMC','ADVENZYMES','AEGISCHEM','AFFLE','AJANTPHARM','ALKYLAMINE','ALLCARGO','AMARAJABAT','AMBER','ANGELONE','ANURAS','APTUS','ASAHIINDIA','ASTERDM','ASTRAZEN','AVANTIFEED','DMART','BASF',
         'BSE','BAJAJELEC','BAJAJHLDNG','BALAMINES','BALRAMCHIN','BANKINDIA','MAHABANK','BAYERCROP','BDL','BEL','BHEL','BIRLACORPN','BSOFT','BLUEDART','BLUESTARCO','BORORENEW','BOSCHLTD','BRIGADE','BCG','MAPMYINDIA'
        ]

target_stocks_list = []
target_stocks = pd.DataFrame()

for stock in stock:
    vol = get_history(symbol=stock,
                  start=start1,
                  end=end1)

    d_vol = pd.concat([vol['Deliverable Volume']])
    symbol_s = pd.concat([vol['Symbol']])
    close = pd.concat([vol['Close']])

    df = pd.DataFrame(symbol_s)
    df['D_vol'] = d_vol

    # print(df)

    cond = df['D_vol'].iloc[-1] > max(df['D_vol'].iloc[-91:-1])

    if(cond):
        target_stocks_list.append(stock)
        target_stocks = pd.concat([target_stocks, df])

print(target_stocks_list)

file_name = f'{datetime.datetime.now().day}-{datetime.datetime.now().month}-{datetime.datetime.now().year}.csv'
target_stocks.to_csv(f'D:/HUGE VOLUME SPURTS/first 250/SEP 2022/{file_name}')
pd.set_option('display.max_columns',10)
pd.set_option('display.max_rows',2000)
print(target_stocks)

报错信息：

Traceback (most recent call last):
  File "C:\Users\Yogesh_PC\PycharmProjects\future oi data analysis\trial2.py", line 64, in <module>
    cond = df['D_vol'].iloc[-1] > max(df['D_vol'].iloc[-91:-1])
  File "C:\python\Python310\lib\site-packages\pandas\core\indexing.py", line 967, in __getitem__
    return self._getitem_axis(maybe_callable, axis=axis)
  File "C:\python\Python310\lib\site-packages\pandas\core\indexing.py", line 1520, in _getitem_axis
    self._validate_integer(key, axis)
  File "C:\python\Python310\lib\site-packages\pandas\core\indexing.py", line 1452, in _validate_integer
    raise IndexError("single positional indexer is out-of-bounds")
IndexError: single positional indexer is out-of-bounds

比如如果股票列表里的'IRCTC'数据没更新，程序就会因为这个股票中断，没法输出其他已更新股票的结果。

修改后的代码

from datetime import date
from datetime import timedelta
from nsepy import get_history
import pandas as pd
import datetime

end1 = date.today()
start1 = end1 - timedelta(days=365)

stock = [
         'RELIANCE','HDFCBANK','INFY','ICICIBANK','HDFC','TCS','KOTAKBANK','LT','SBIN','HINDUNILVR','AXISBANK','ITC','BAJFINANCE','BHARTIARTL','ASIANPAINT','HCLTECH','MARUTI','TITAN','BAJAJFINSV','TATAMOTORS',
         'TECHM','SUNPHARMA','TATASTEEL','M&M','WIPRO','ULTRACEMCO','POWERGRID','HINDALCO','NTPC','NESTLEIND','GRASIM','ONGC','JSWSTEEL','HDFCLIFE','INDUSINDBK','SBILIFE','DRREDDY','ADANIPORTS','DIVISLAB','CIPLA',
         'BAJAJ-AUTO','TATACONSUM','UPL','BRITANNIA','BPCL','EICHERMOT','HEROMOTOCO','COALINDIA','SHREECEM','IOC','VEDL','ADANIENT', 'APOLLOHOSP', 'TATAPOWER', 'PIDILITIND', 'SRF', 'NAUKRI', 'ICICIGI', 'DABUR',
         'GODREJCP', 'HAVELLS', 'PEL', 'VOLTAS', 'AUBANK', 'LTI', 'CHOLAFIN', 'AMBUJACEM', 'MARICO', 'SRTRANSFIN','GAIL', 'MCDOWELL-N', 'MPHASIS', 'MINDTREE', 'PAGEIND', 'ZEEL', 'BEL', 'TRENT', 'CROMPTON', 'JUBLFOOD',
         'DLF', 'SBICARD', 'SIEMENS', 'BANDHANBNK', 'IRCTC', 'LAURUSLABS', 'PIIND', 'INDIGO', 'INDUSTOWER','ICICIPRULI', 'MOTHERSON', 'AARTIIND', 'FEDERALBNK', 'BANKBARODA', 'PERSISTENT', 'HINDPETRO', 'ACC',
         'AUROPHARMA', 'COLPAL', 'GODREJPROP', 'MFSL', 'LUPIN', 'BIOCON', 'ASHOKLEY', 'BHARATFORG', 'BERGEPAINT','JINDALSTEL', 'ASTRAL', 'IEX', 'NMDC', 'CONCOR', 'INDHOTEL', 'BALKRISIND', 'PETRONET', 'CANBK', 'ALKEM',
         'DIXON', 'DEEPAKNTR', 'DALBHARAT', 'TVSMOTOR', 'ATUL', 'HDFCAMC', 'TATACOMM', 'MUTHOOTFIN', 'TATACHEM','SAIL', 'IDFCFIRSTB', 'PFC', 'BOSCHLTD', 'MRF', 'NAVINFLUOR', 'CUMMINSIND', 'IGL', 'IPCALAB', 'COFORGE',
         'ESCORTS', 'TORNTPHARM', 'LTTS', 'RECLTD', 'LICHSGFIN', 'BATAINDIA', 'HAL', 'PNB', 'GUJGASLTD', 'UBL','3MINDIA','ABB','AIAENG','APLAPOLLO','AARTIDRUGS','AAVAS','ABBOTINDIA','ADANIGREEN','ATGL','ABCAPITAL',
         'ABFRL','ABSLAMC','ADVENZYMES','AEGISCHEM','AFFLE','AJANTPHARM','ALKYLAMINE','ALLCARGO','AMARAJABAT','AMBER','ANGELONE','ANURAS','APTUS','ASAHIINDIA','ASTERDM','ASTRAZEN','AVANTIFEED','DMART','BASF',
         'BSE','BAJAJELEC','BAJAJHLDNG','BALAMINES','BALRAMCHIN','BANKINDIA','MAHABANK','BAYERCROP','BDL','BEL','BHEL','BIRLACORPN','BSOFT','BLUEDART','BLUESTARCO','BORORENEW','BOSCHLTD','BRIGADE','BCG','MAPMYINDIA'
        ]

target_stocks_list = []
target_stocks = pd.DataFrame()

for stock_sym in stock:
    try:
        vol = get_history(symbol=stock_sym,
                      start=start1,
                      end=end1)
        
        # 检查返回的DataFrame是否为空
        if vol.empty:
            print(f"无数据，跳过股票: {stock_sym}")
            continue
        
        # 直接提取列构造DataFrame，无需多余的pd.concat
        df = pd.DataFrame({
            'Symbol': vol['Symbol'],
            'D_vol': vol['Deliverable Volume']
        })
        
        # 确保数据长度足够，避免索引越界
        if len(df) < 91:
            print(f"数据不足91条，跳过股票: {stock_sym}")
            continue
        
        # 计算条件，使用pandas内置max方法更高效
        latest_vol = df['D_vol'].iloc[-1]
        past_90_max = df['D_vol'].iloc[-91:-1].max()
        
        if latest_vol > past_90_max:
            target_stocks_list.append(stock_sym)
            target_stocks = pd.concat([target_stocks, df])
            
    except Exception as e:
        print(f"处理股票 {stock_sym} 时出错: {str(e)}")
        continue

print(target_stocks_list)

file_name = f'{datetime.datetime.now().day}-{datetime.datetime.now().month}-{datetime.datetime.now().year}.csv'
target_stocks.to_csv(f'D:/HUGE VOLUME SPURTS/first 250/SEP 2022/{file_name}')
pd.set_option('display.max_columns',10)
pd.set_option('display.max_rows',2000)
print(target_stocks)

关键修复点

异常捕获机制：用try-except包裹单只股票的处理逻辑，任何异常都会触发跳过操作，保证程序继续处理下一只股票。
空数据校验：调用接口后先判断返回的数据集是否为空，为空直接跳过该股票。
数据长度检查：确保数据至少有91条记录，避免iloc[-91:-1]出现索引越界问题。
代码优化：去掉不必要的pd.concat操作，直接用字典构造DataFrame；替换Python内置max()为pandas的max()方法，提升处理效率。
变量名修正：将循环变量从stock改为stock_sym，避免与股票列表变量名冲突。

内容的提问来源于stack exchange，提问作者user19696249