我在python上运行了以下代码,以便从一开始就检索各种加密货币收盘价。我使用以下代码成功运行它:
tickers = ['USDT_BTC','USDT_BCH','USDT_ETC','USDT_XMR','USDT_ETH','USDT_DASH',
'USDT_XRP','USDT_LTC','USDT_NXT','USDT_STR','USDT_REP','USDT_ZEC']
我现在已将其更改为如下(包括完整代码)并获得ValueError。
[LN1]
def CryptoDataCSV(symbol, frequency):
#Params: String symbol, int frequency = 300,900,1800,7200,14400,86400
#Returns: df from first available date
url ='https://poloniex.com/public?command=returnChartData¤cyPair='+symbol+'&end=9999999999&period='+str(frequency)+'&start=0'
df = pd.read_json(url)
df.set_index('date',inplace=True)
df.to_csv(symbol + '.csv')
print('Processed: ' + symbol)
[LN2]
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
[LN3]
tickers = 'ETH_BTC','STR_BTC','XMR_BTC','XRP_BTC','LTC_BTC','DASH_BTC',
'ETC_BTC','POT_BTC','OMG_BTC','FCT_BTC','ZEC_BTC','BTS_BTC','VTC_BTC',
'XEM_BTC','MAID_BTC','DGB_BTC','STRAT_BTC','LSK_BTC','XVC_BTC','SC_BTC',
'DOGE_BTC','XBC_BTC','GNT_BTC','EMC2_BTC','CLAM_BTC','RIC_BTC','SYS_BTC',
'DCR_BTC','STEEM_BTC','ZRX_BTC','GAME_BTC','VIA_BTC','NXC_BTC','NXT_BTC'
,'VRC_BTC','NAV_BTC','PINK_BTC','STORJ_BTC','ARDR_BTC','BCN_BTC','CVC_BTC',
'EXP_BTC','LBC_BTC','GNO_BTC','GAS_BTC','OMNI_BTC','XCP_BTC','NEOS_BTC',
'BURST_BTC','AMP_BTC','FLDC_BTC','FLO_BTC','SBD_BTC','BLK_BTC','BTCD_BTC',
'NOTE_BTC','GRC_BTC','PPC_BTC','BTM_BTC','XPM_BTC','NMC_BTC','PASC_BTC',
'NAUT_BTC','BELA_BTC','SJCX_BTC','HUC_BTC','RADS_BTC']
[LN4]
for ticker in tickers:
CryptoDataCSV(ticker, 86400)
我现在收到以下错误:
----------------------------------------------- ---------------------------- ValueError Traceback(最近一次调用 最后)in() 1代表股票代码: ----> 2 CryptoDataCSV(自动收报机,86400)
CryptoDataCSV中的(符号,频率) 7 url ='https://poloniex.com/public?command=returnChartData¤cyPair='+ symbol +'& end = 9999999999& period ='+ str(frequency)+'& start = 0' 8 ----> 9 df = pd.read_json(url) 10 11 df.set_index('date',inplace = True)
〜\ Anaconda3 \ lib \ site-packages \ pandas \ io \ json \ json.py in read_json(path_or_buf,orient,typ,dtype,convert_axes, convert_dates,keep_default_dates,numpy,precise_float,date_unit, 编码,线) 352 obj = FrameParser(json,orient,dtype,convert_axes,convert_dates, 353 keep_default_dates,numpy,precise_float, - > 354 date_unit).parse() 355 356如果typ =='series'或obj是None:
解析中的〜\ Anaconda3 \ lib \ site-packages \ pandas \ io \ json \ json.py(个体经营) 420 421其他: - > 422 self._parse_no_numpy() 423 424如果self.obj为None:
〜\ Anaconda3 \ lib \ site-packages \ pandas \ io \ json \ json.py in _parse_no_numpy(个体经营) 637如果orient ==“columns”: 638 self.obj = DataFrame( - > 639次加载(json,precise_float = self.precise_float),dtype = None) 640 elif orient ==“split”: 641 decoding = dict((str(k),v)
init 中的〜\ Anaconda3 \ lib \ site-packages \ pandas \ core \ frame.py(自我, 数据,索引,列,dtype,副本) 273 dtype = dtype,copy = copy) 274 elif isinstance(data,dict): - > 275 mgr = self._init_dict(data,index,columns,dtype = dtype) 276 elif isinstance(data,ma.MaskedArray): 277将numpy.ma.mrecords导入为mrecords
_init_dict中的〜\ Anaconda3 \ lib \ site-packages \ pandas \ core \ frame.py(self, 数据,索引,列,dtype) 409个数组= [键中k的数据[k]] 410 - > 411 return _arrays_to_mgr(arrays,data_names,index,columns,dtype = dtype) 412 413 def _init_ndarray(self,values,index,columns,dtype = None,copy = False):
〜\ Anaconda3 \ lib \ site-packages \ pandas \ core \ frame.py in _arrays_to_mgr(arrays,arr_names,index,columns,dtype)5494#计算索引,如果需要5495,如果index为None: - > 5496 index = extract_index(arrays)5497 else:5498 index = _ensure_index(index)
〜\ Anaconda3 \ lib \ site-packages \ pandas \ core \ frame.py in extract_index(data)5533 5534如果不是索引而不是 raw_lengths: - > 5535引发ValueError('如果使用所有标量值,则必须传递'5536'一个索引')5537
ValueError:如果使用所有标量值,则必须传递索引
答案 0 :(得分:2)
我刚测试了你的数据,看来你的一些货币对根本不起作用,返回一个形式的json:
{"error":"Invalid currency pair."}
如果返回此内容,pd.read_json
会抛出错误,因为它无法将其转换为数据框。
最简单的解决方法是使用try-except
大括号并处理任何非工作代码。
broken_tickers = []
for t in tickers:
url ='https://poloniex.com/public?command=returnChartData¤cyPair={}&end=9999999999&period={}&start=0'.format(t, 86400)
try:
df = pd.read_json(url)
except ValueError:
broken_tickers.append(t)
continue
df.set_index('date')
df.to_csv('{}.csv'.format(t))
我已经摆脱了这个功能,我觉得这里没有必要,但你可以把它重新加入。