pandas 从谷歌财经下载股票数据
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Download stocks data from google finance
提问by Filipe Ferminiano
I'm trying to download data from Google Finance from a list of stocks symbols inside a .csv file.
我正在尝试从 .csv 文件中的股票代码列表中下载来自 Google Finance 的数据。
This is the class that I'm trying to adapt from this site:
这是我试图从这个网站改编的课程：
import urllib,time,datetime
import csv
class Quote(object):
DATE_FMT = '%Y-%m-%d'
TIME_FMT = '%H:%M:%S'
def __init__(self):
self.symbol = ''
self.date,self.time,self.open_,self.high,self.low,self.close,self.volume = ([] for _ in range(7))
def append(self,dt,open_,high,low,close,volume):
self.date.append(dt.date())
self.time.append(dt.time())
self.open_.append(float(open_))
self.high.append(float(high))
self.low.append(float(low))
self.close.append(float(close))
self.volume.append(int(volume))
def append_csv(self, filename):
with open(filename, 'a') as f:
f.write(self.to_csv())
def __repr__(self):
return self.to_csv()
def get_symbols(self, filename):
for line in open(filename,'r'):
if line != 'codigo':
print line
q = GoogleQuote(line,'2014-01-01','2014-06-20')
q.append_csv('data.csv')
class GoogleQuote(Quote):
''' Daily quotes from Google. Date format='yyyy-mm-dd' '''
def __init__(self,symbol,start_date,end_date=datetime.date.today().isoformat()):
super(GoogleQuote,self).__init__()
self.symbol = symbol.upper()
start = datetime.date(int(start_date[0:4]),int(start_date[5:7]),int(start_date[8:10]))
end = datetime.date(int(end_date[0:4]),int(end_date[5:7]),int(end_date[8:10]))
url_string = "http://www.google.com/finance/historical?q={0}".format(self.symbol)
url_string += "&startdate={0}&enddate={1}&output=csv".format(
start.strftime('%b %d, %Y'),end.strftime('%b %d, %Y'))
csv = urllib.urlopen(url_string).readlines()
csv.reverse()
for bar in xrange(0,len(csv)-1):
try:
#ds,open_,high,low,close,volume = csv[bar].rstrip().split(',')
#open_,high,low,close = [float(x) for x in [open_,high,low,close]]
#dt = datetime.datetime.strptime(ds,'%d-%b-%y')
#self.append(dt,open_,high,low,close,volume)
data = csv[bar].rstrip().split(',')
dt = datetime.datetime.strftime(data[0],'%d-%b-%y')
close = data[4]
self.append(dt,close)
except:
print "error " + str(len(csv)-1)
print "error " + csv[bar]
if __name__ == '__main__':
q = Quote() # create a generic quote object
q.get_symbols('list.csv')
But, for some quotes, the code doesn't return all data (e.g. BIOM3), some fields return as '-'. How can I handle the split in these cases? For last, at some point of the script, it stops of download the data because the script stops, it doesn't return any message. How can I handle this problem?
但是，对于某些引号，代码不会返回所有数据（例如 BIOM3），某些字段返回为“-”。在这些情况下，我该如何处理拆分？最后，在脚本的某个时刻，它停止下载数据，因为脚本停止，它不返回任何消息。我该如何处理这个问题？
采纳答案by CT Zhu
It should work, but notice that the ticker should be: BVMF:ABRE11
它应该可以工作，但请注意代码应该是：BVMF:ABRE11
In [250]:
import pandas.io.data as web
import datetime
start = datetime.datetime(2010, 1, 1)
end = datetime.datetime(2013, 1, 27)
df=web.DataReader("BVMF:ABRE11", 'google', start, end)
print df.head(10)
Open High Low Close Volume
?Date
2011-07-26 19.79 19.79 18.30 18.50 1843700
2011-07-27 18.45 18.60 17.65 17.89 1475100
2011-07-28 18.00 18.50 18.00 18.30 441700
2011-07-29 18.30 18.84 18.20 18.70 392800
2011-08-01 18.29 19.50 18.29 18.86 217800
2011-08-02 18.86 18.86 18.60 18.80 154600
2011-08-03 18.90 18.90 18.00 18.00 168700
2011-08-04 17.50 17.85 16.50 16.90 238700
2011-08-05 17.00 17.00 15.63 16.00 253000
2011-08-08 15.50 15.96 14.35 14.50 224300
[10 rows x 5 columns]
In [251]:
df=web.DataReader("BVMF:BIOM3", 'google', start, end)
print df.head(10)
Open High Low Close Volume
?Date
2010-01-04 2.90 2.90 2.90 2.90 0
2010-01-05 3.00 3.00 3.00 3.00 0
2010-01-06 3.01 3.01 3.01 3.01 0
2010-01-07 3.01 3.09 3.01 3.09 2000
2010-01-08 3.01 3.01 3.01 3.01 0
2010-01-11 3.00 3.00 3.00 3.00 0
2010-01-12 3.00 3.00 3.00 3.00 0
2010-01-13 3.00 3.10 3.00 3.00 7000
2010-01-14 3.00 3.00 3.00 3.00 0
2010-01-15 3.00 3.00 3.00 3.00 1000
[10 rows x 5 columns]
