Это была проблема с кодом примера. Если вы перейдете на главную страницу GitHub, вы получите последнюю версию — даже небольшие обновления.
Я немного модифицировал client.py
и проблем с выводом не было.
#!/usr/bin/env python
# coding: utf-8
import requests
from datetime import datetime
import pandas as pd
def get_price_data(query):
r = requests.get(
"https://finance.google.com/finance/getprices", params=query)
lines = r.text.splitlines()
data = []
index = []
basetime = 0
for price in lines:
cols = price.split(",")
if cols[0][0] == 'a':
basetime = int(cols[0][1:])
index.append(datetime.fromtimestamp(basetime))
data.append([float(cols[4]), float(cols[2]), float(
cols[3]), float(cols[1]), int(cols[5])])
elif cols[0][0].isdigit():
date = basetime + (int(cols[0]) * int(query['i']))
index.append(datetime.fromtimestamp(date))
data.append([float(cols[4]), float(cols[2]), float(
cols[3]), float(cols[1]), int(cols[5])])
return pd.DataFrame(data, index=index, columns=['Open', 'High', 'Low', 'Close', 'Volume'])
def get_closing_data(queries, period):
closing_data = []
for query in queries:
query['i'] = 86400
query['p'] = period
r = requests.get(
"https://finance.google.com/finance/getprices", params=query)
lines = r.text.splitlines()
data = []
index = []
basetime = 0
for price in lines:
cols = price.split(",")
if cols[0][0] == 'a':
basetime = int(cols[0][1:])
date = basetime
data.append(float(cols[1]))
index.append(datetime.fromtimestamp(date).date())
elif cols[0][0].isdigit():
date = basetime + (int(cols[0]) * int(query['i']))
data.append(float(cols[1]))
index.append(datetime.fromtimestamp(date).date())
s = pd.Series(data, index=index, name=query['q'])
closing_data.append(s[~s.index.duplicated(keep='last')])
return pd.concat(closing_data, axis=1)
def get_open_close_data(queries, period):
open_close_data = pd.DataFrame()
for query in queries:
query['i'] = 86400
query['p'] = period
r = requests.get(
"https://finance.google.com/finance/getprices", params=query)
lines = r.text.splitlines()
data = []
index = []
basetime = 0
for price in lines:
cols = price.split(",")
if cols[0][0] == 'a':
basetime = int(cols[0][1:])
date = basetime
data.append([float(cols[4]), float(cols[1])])
index.append(datetime.fromtimestamp(date).date())
elif cols[0][0].isdigit():
date = basetime + (int(cols[0]) * int(query['i']))
data.append([float(cols[4]), float(cols[1])])
index.append(datetime.fromtimestamp(date).date())
df = pd.DataFrame(data, index=index, columns=[
query['q'] + '_Open', query['q'] + '_Close'])
open_close_data = pd.concat(
[open_close_data, df[~df.index.duplicated(keep='last')]], axis=1)
return open_close_data
def get_prices_data(queries, period):
prices_data = pd.DataFrame()
for query in queries:
query['i'] = 86400
query['p'] = period
r = requests.get(
"https://finance.google.com/finance/getprices", params=query)
lines = r.text.splitlines()
data = []
index = []
basetime = 0
for price in lines:
cols = price.split(",")
if cols[0][0] == 'a':
basetime = int(cols[0][1:])
date = basetime
data.append([float(cols[4]), float(cols[2]), float(
cols[3]), float(cols[1]), int(cols[5])])
index.append(datetime.fromtimestamp(date).date())
elif cols[0][0].isdigit():
date = basetime + (int(cols[0]) * int(query['i']))
data.append([float(cols[4]), float(cols[2]), float(
cols[3]), float(cols[1]), int(cols[5])])
index.append(datetime.fromtimestamp(date).date())
df = pd.DataFrame(data, index=index, columns=[
query['q'] + '_Open', query['q'] + '_High', query['q'] + '_Low', query['q'] + '_Close', query['q'] + '_Volume'])
prices_data = pd.concat(
[prices_data, df[~df.index.duplicated(keep='last')]], axis=1)
return prices_data
def get_prices_time_data(queries, period, interval):
prices_time_data = pd.DataFrame()
for query in queries:
query['i'] = interval
query['p'] = period
r = requests.get(
"https://finance.google.com/finance/getprices", params=query)
lines = r.text.splitlines()
data = []
index = []
basetime = 0
for price in lines:
cols = price.split(",")
if cols[0][0] == 'a':
basetime = int(cols[0][1:])
date = basetime
data.append([float(cols[4]), float(cols[2]), float(
cols[3]), float(cols[1]), int(cols[5])])
index.append(datetime.fromtimestamp(date))
elif cols[0][0].isdigit():
date = basetime + (int(cols[0]) * int(query['i']))
data.append([float(cols[4]), float(cols[2]), float(
cols[3]), float(cols[1]), int(cols[5])])
index.append(datetime.fromtimestamp(date))
df = pd.DataFrame(data, index=index, columns=[
query['q'] + '_Open', query['q'] + '_High', query['q'] + '_Low', query['q'] + '_Close', query['q'] + '_Volume'])
prices_time_data = pd.concat(
[prices_time_data, df[~df.index.duplicated(keep='last')]], axis=1)
return prices_time_data
Фрагмент
params = {
'q': ".DJI", # Stock symbol (ex: "AAPL")
'i': "86400", # Interval size in seconds ("86400" = 1 day intervals)
# Stock exchange symbol on which stock is traded (ex: "NASD")
'x': "INDEXDJX",
'p': "1Y" # Period (Ex: "1Y" = 1 year)
}
df = get_price_data(params)
print(df)
Вывод
Volume Open High ... Close
328405532 01.08.2017 15:00:00 21961.42 21990.96 ... 21963.92
328405532 02.08.2017 15:00:00 22004.36 22036.10 ... 22016.24
336824836 2017-08-03 15:00:00 22007.58 22044.85 ... 22026.10
278731064 2017-08-04 15:00:00 22058.39 22092.81 ... 22092.81
253635270 2017-08-07 15:00: 00 22100.20 22121.15 ... 22118.42
213012378 08.08.2017 15:00:00 22095.14 22179.11 ... 22085.34
person
Noah M.
schedule
01.08.2018
nd ...</span><br></div></div><div class="g"><h3 class="r"><a href="/url?q=https://en.wikipedia.org/wiki/DJI_(company)&sa=U&ved=0ahUKEwiB-e_gjMzcAhUpwlkKHTTUC74QFghGMAw&usg=AOvVaw1ugw
определенно не целое число. Мне кажется, что вы неправильно анализируете данные. Не могли бы вы опубликовать необработанные данные, полученные от Google? - person Noah M.   schedule 01.08.2018YQLResponseMalformedError: Response malformed.
- person Raksha   schedule 01.08.2018fix-yahoo-finance
вроде работает нормально - person Raksha   schedule 01.08.2018