无法使用 pandas_datareader 从雅虎获取股票数据
Unable to get stock data from yahoo with pandas_datareader
这是我的代码：
start = '2015-1-1'
end = '2020-12-31'
source = 'yahoo'
google = data.DataReader('GOOG', start=start, end=end, data_source=source).reset_index()
直到上个月我一直在使用这段代码并且它工作正常，一个月后我尝试了这段代码但现在这段代码抛出了错误：
Unable to read URL: https://finance.yahoo.com/quote/GOOG/history?period1=1420065000&period2=1609453799&interval=1d&frequency=1d&filter=history
我想不通，请你解释一下，为什么会这样？
雅虎！ Finance 使用 pandas 提供正确的输出，没有任何问题。
脚本：
import pandas as pd
import requests
link = 'https://finance.yahoo.com/quote/GOOG/history?period1=1420065000&period2=1609453799&interval=1d&frequency=1d&filter=history'
r = requests.get(link, headers = {'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'})
data = pd.read_html(r.text)[0]
df =pd.DataFrame(data)
df=df.iloc[0:100]
print(df)
输出：
Date Open High Low Close AdjClose Volume
Dec 31, 2020 1735.42 1758.93 1735.42 1751.88 1751.88 1011900
Dec 30, 2020 1762.01 1765.09 1725.6 1739.52 1739.52 1306100
Dec 29, 2020 1787.79 1792.44 1756.09 1758.72 1758.72 1299400
Dec 28, 2020 1751.64 1790.73 1746.33 1776.09 1776.09 1393000
Dec 24, 2020 1735 1746 1729.11 1738.85 1738.85 346800
Dec 23, 2020 1728.11 1747.99 1725.04 1732.38 1732.38 1033800
Dec 22, 2020 1734.43 1737.41 1712.57 1723.5 1723.5 936700
Dec 21, 2020 1713.51 1740.85 1699 1739.37 1739.37 1828400
Dec 18, 2020 1754.18 1755.11 1720.22 1731.01 1731.01 4016400
Dec 17, 2020 1768.51 1771.78 1738.66 1747.9 1747.9 1624700
Dec 16, 2020 1772.88 1773 1756.08 1763 1763 1513500
Dec 15, 2020 1764.42 1771.42 1749.95 1767.77 1767.77 1482300
Dec 14, 2020 1775 1797.39 1757.21 1760.06 1760.06 1600200
Dec 11, 2020 1763.06 1784.45 1760 1781.77 1781.77 1220700
Dec 10, 2020 1769.8 1781.31 1740.32 1775.33 1775.33 1362800
Dec 09, 2020 1812.01 1834.27 1767.81 1784.13 1784.13 1507600
Dec 08, 2020 1810.1 1821.9 1796.2 1818.55 1818.55 1096300
Dec 07, 2020 1819 1832.37 1805.78 1819.48 1819.48 1320900
Dec 04, 2020 1824.52 1833.16 1816.99 1827.99 1827.99 1378200
Dec 03, 2020 1824.01 1847.2 1822.65 1826.77 1826.77 1227300
Dec 02, 2020 1798.1 1835.65 1789.47 1827.95 1827.95 1222000
Dec 01, 2020 1774.37 1824.83 1769.37 1798.1 1798.1 1736900
Nov 30, 2020 1781.18 1788.06 1755 1760.74 1760.74 1823800
Nov 27, 2020 1773.09 1804 1772.44 1793.19 1793.19 884900
Nov 25, 2020 1772.89 1778.54 1756.54 1771.43 1771.43 1045800
Nov 24, 2020 1730.5 1771.6 1727.69 1768.88 1768.88 1578000
Nov 23, 2020 1749.6 1753.9 1717.72 1734.86 1734.86 2161600
Nov 20, 2020 1765.21 1774 1741.86 1742.19 1742.19 2313500
Nov 19, 2020 1738.38 1769.59 1737.01 1763.92 1763.92 1249900
Nov 18, 2020 1765.23 1773.47 1746.14 1746.78 1746.78 1173500
Nov 17, 2020 1776.94 1785 1767 1770.15 1770.15 1147100
Nov 16, 2020 1771.7 1799.07 1767.69 1781.38 1781.38 1246800
Nov 13, 2020 1757.63 1781.04 1744.55 1777.02 1777.02 1499900
Nov 12, 2020 1747.63 1768.27 1745.6 1749.84 1749.84 1247500
Nov 11, 2020 1750 1764.22 1747.36 1752.71 1752.71 1264000
Nov 10, 2020 1731.09 1763 1717.3 1740.39 1740.39 2636100
Nov 09, 2020 1790.9 1818.06 1760.02 1763 1763 2268300
Nov 06, 2020 1753.95 1772.43 1740.35 1761.75 1761.75 1660900
Nov 05, 2020 1781 1793.64 1750.51 1763.37 1763.37 2065800
Nov 04, 2020 1710.28 1771.36 1706.03 1749.13 1749.13 3570900
Nov 03, 2020 1631.78 1661.7 1616.62 1650.21 1650.21 1661700
Nov 02, 2020 1628.16 1660.77 1616.03 1626.03 1626.03 2535400
Oct 30, 2020 1672.11 1687 1604.46 1621.01 1621.01 4329100
Oct 29, 2020 1522.36 1593.71 1522.24 1567.24 1567.24 2003100
Oct 28, 2020 1559.74 1561.35 1514.62 1516.62 1516.62 1834000
Oct 27, 2020 1595.67 1606.84 1582.78 1604.26 1604.26 1229000
Oct 26, 2020 1625.01 1638.24 1576.5 1590.45 1590.45 1853300
Oct 23, 2020 1626.07 1642.36 1620.51 1641 1641 1375800
Oct 22, 2020 1593.05 1621.99 1585 1615.33 1615.33 1433600
Oct 21, 2020 1573.33 1618.73 1571.63 1593.31 1593.31 2568300
Oct 20, 2020 1527.05 1577.5 1525.67 1555.93 1555.93 2241700
Oct 19, 2020 1580.46 1588.15 1528 1534.61 1534.61 1607100
Oct 16, 2020 1565.85 1581.13 1563 1573.01 1573.01 1434700
Oct 15, 2020 1547.15 1575.1 1545.03 1559.13 1559.13 1540000
Oct 14, 2020 1578.59 1587.68 1550.53 1568.08 1568.08 1929300
Oct 13, 2020 1583.73 1590 1563.2 1571.68 1571.68 1601000
Oct 12, 2020 1543 1593.86 1532.57 1569.15 1569.15 2482600
Oct 09, 2020 1494.7 1516.52 1489.45 1515.22 1515.22 1435300
Oct 08, 2020 1465.09 1490 1465.09 1485.93 1485.93 1187800
Oct 07, 2020 1464.29 1468.96 1436 1460.29 1460.29 1746200
Oct 06, 2020 1475.58 1486.76 1448.59 1453.44 1453.44 1245400
Oct 05, 2020 1466.21 1488.21 1464.27 1486.02 1486.02 1113300
Oct 02, 2020 1462.03 1483.2 1450.92 1458.42 1458.42 1284100
Oct 01, 2020 1484.27 1499.04 1479.21 1490.09 1490.09 1779500
Sep 30, 2020 1466.8 1489.75 1459.88 1469.6 1469.6 1701600
Sep 29, 2020 1470.39 1476.66 1458.81 1469.33 1469.33 978200
Sep 28, 2020 1474.21 1476.8 1449.3 1464.52 1464.52 2007900
Sep 25, 2020 1432.63 1450 1413.34 1444.96 1444.96 1323000
Sep 24, 2020 1411.03 1443.71 1409.85 1428.29 1428.29 1450200
Sep 23, 2020 1458.78 1460.96 1407.7 1415.21 1415.21 1657400
Sep 22, 2020 1450.09 1469.52 1434.53 1465.46 1465.46 1583200
Sep 21, 2020 1440.06 1448.36 1406.55 1431.16 1431.16 2888800
Sep 18, 2020 1498.01 1503 1437.13 1459.99 1459.99 3103900
Sep 17, 2020 1496 1508.3 1470 1495.53 1495.53 1879800
Sep 16, 2020 1555.54 1562 1519.82 1520.9 1520.9 1311700
Sep 15, 2020 1536 1559.57 1531.83 1541.44 1541.44 1331100
Sep 14, 2020 1539.01 1564 1515.74 1519.28 1519.28 1696600
Sep 11, 2020 1536 1575.2 1497.36 1520.72 1520.72 1597100
Sep 10, 2020 1560.64 1584.08 1525.81 1532.02 1532.02 1618600
Sep 09, 2020 1557.53 1569 1536.05 1556.96 1556.96 1774700
Sep 08, 2020 1533.51 1563.86 1528.01 1532.39 1532.39 2610900
Sep 04, 2020 1624.26 1645.11 1547.61 1591.04 1591.04 2608600
Sep 03, 2020 1709.71 1709.71 1615.06 1641.84 1641.84 3107800
Sep 02, 2020 1673.78 1733.18 1666.33 1728.28 1728.28 2511200
Sep 01, 2020 1636.63 1665.73 1632.22 1660.71 1660.71 1825300
Aug 31, 2020 1647.89 1647.96 1630.31 1634.18 1634.18 1823400
Aug 28, 2020 1633.49 1647.17 1630.75 1644.41 1644.41 1499000
Aug 27, 2020 1653.68 1655 1625.75 1634.33 1634.33 1861600
Aug 26, 2020 1608 1659.22 1603.6 1652.38 1652.38 3993400
Aug 25, 2020 1582.07 1611.62 1582.07 1608.22 1608.22 2247100
Aug 24, 2020 1593.98 1614.17 1580.57 1588.2 1588.2 1409900
Aug 21, 2020 1577.03 1597.72 1568.01 1580.42 1580.42 1446500
Aug 20, 2020 1543.45 1585.87 1538.2 1581.75 1581.75 1706900
Aug 19, 2020 1553.31 1573.68 1543.95 1547.53 1547.53 1660600
Aug 18, 2020 1526.18 1562.47 1523.71 1558.6 1558.6 2027100
Aug 17, 2020 1514.67 1525.61 1507.97 1517.98 1517.98 1378300
Aug 14, 2020 1515.66 1521.9 1502.88 1507.73 1507.73 1354800
Aug 13, 2020 1510.34 1537.25 1508.01 1518.45 1518.45 1455200
Aug 12, 2020 1485.58 1512.39 1485.25 1506.62 1506.62 1437000
Aug 11, 2020 1492.44 1510 1478 1480.32 1480.32 1454400
Yahoo Finance 已停用其 API。试试这个 python library.
雅虎！财务略微改变了他们的结构。 现在需要 headers 用于 http 请求的数据检索。完成后效果很好。
对于 pandas 和 pandas-datareader，如果您使用它，您需要 升级 它们。 （已经排序）。可能在所有其他使用来自 yahoo!例如 backtrader 等，您需要在 yahoo! 上升级或添加 headers检索数据的脚本:).
pip install --upgrade pandas
pip install --upgrade pandas-datareader
祝你有愉快的一天 ;).
请将 pandas_datareader 升级到 >= 0.10.0 的版本。根据 release notes.
，此错误已在 0.10.0 中修复
Fixed Yahoo readers which now require headers
这是我的代码：
start = '2015-1-1'
end = '2020-12-31'
source = 'yahoo'
google = data.DataReader('GOOG', start=start, end=end, data_source=source).reset_index()
直到上个月我一直在使用这段代码并且它工作正常，一个月后我尝试了这段代码但现在这段代码抛出了错误：
Unable to read URL: https://finance.yahoo.com/quote/GOOG/history?period1=1420065000&period2=1609453799&interval=1d&frequency=1d&filter=history
我想不通，请你解释一下，为什么会这样？
雅虎！ Finance 使用 pandas 提供正确的输出，没有任何问题。
脚本：
import pandas as pd
import requests
link = 'https://finance.yahoo.com/quote/GOOG/history?period1=1420065000&period2=1609453799&interval=1d&frequency=1d&filter=history'
r = requests.get(link, headers = {'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'})
data = pd.read_html(r.text)[0]
df =pd.DataFrame(data)
df=df.iloc[0:100]
print(df)
输出：
Date Open High Low Close AdjClose Volume
Dec 31, 2020 1735.42 1758.93 1735.42 1751.88 1751.88 1011900
Dec 30, 2020 1762.01 1765.09 1725.6 1739.52 1739.52 1306100
Dec 29, 2020 1787.79 1792.44 1756.09 1758.72 1758.72 1299400
Dec 28, 2020 1751.64 1790.73 1746.33 1776.09 1776.09 1393000
Dec 24, 2020 1735 1746 1729.11 1738.85 1738.85 346800
Dec 23, 2020 1728.11 1747.99 1725.04 1732.38 1732.38 1033800
Dec 22, 2020 1734.43 1737.41 1712.57 1723.5 1723.5 936700
Dec 21, 2020 1713.51 1740.85 1699 1739.37 1739.37 1828400
Dec 18, 2020 1754.18 1755.11 1720.22 1731.01 1731.01 4016400
Dec 17, 2020 1768.51 1771.78 1738.66 1747.9 1747.9 1624700
Dec 16, 2020 1772.88 1773 1756.08 1763 1763 1513500
Dec 15, 2020 1764.42 1771.42 1749.95 1767.77 1767.77 1482300
Dec 14, 2020 1775 1797.39 1757.21 1760.06 1760.06 1600200
Dec 11, 2020 1763.06 1784.45 1760 1781.77 1781.77 1220700
Dec 10, 2020 1769.8 1781.31 1740.32 1775.33 1775.33 1362800
Dec 09, 2020 1812.01 1834.27 1767.81 1784.13 1784.13 1507600
Dec 08, 2020 1810.1 1821.9 1796.2 1818.55 1818.55 1096300
Dec 07, 2020 1819 1832.37 1805.78 1819.48 1819.48 1320900
Dec 04, 2020 1824.52 1833.16 1816.99 1827.99 1827.99 1378200
Dec 03, 2020 1824.01 1847.2 1822.65 1826.77 1826.77 1227300
Dec 02, 2020 1798.1 1835.65 1789.47 1827.95 1827.95 1222000
Dec 01, 2020 1774.37 1824.83 1769.37 1798.1 1798.1 1736900
Nov 30, 2020 1781.18 1788.06 1755 1760.74 1760.74 1823800
Nov 27, 2020 1773.09 1804 1772.44 1793.19 1793.19 884900
Nov 25, 2020 1772.89 1778.54 1756.54 1771.43 1771.43 1045800
Nov 24, 2020 1730.5 1771.6 1727.69 1768.88 1768.88 1578000
Nov 23, 2020 1749.6 1753.9 1717.72 1734.86 1734.86 2161600
Nov 20, 2020 1765.21 1774 1741.86 1742.19 1742.19 2313500
Nov 19, 2020 1738.38 1769.59 1737.01 1763.92 1763.92 1249900
Nov 18, 2020 1765.23 1773.47 1746.14 1746.78 1746.78 1173500
Nov 17, 2020 1776.94 1785 1767 1770.15 1770.15 1147100
Nov 16, 2020 1771.7 1799.07 1767.69 1781.38 1781.38 1246800
Nov 13, 2020 1757.63 1781.04 1744.55 1777.02 1777.02 1499900
Nov 12, 2020 1747.63 1768.27 1745.6 1749.84 1749.84 1247500
Nov 11, 2020 1750 1764.22 1747.36 1752.71 1752.71 1264000
Nov 10, 2020 1731.09 1763 1717.3 1740.39 1740.39 2636100
Nov 09, 2020 1790.9 1818.06 1760.02 1763 1763 2268300
Nov 06, 2020 1753.95 1772.43 1740.35 1761.75 1761.75 1660900
Nov 05, 2020 1781 1793.64 1750.51 1763.37 1763.37 2065800
Nov 04, 2020 1710.28 1771.36 1706.03 1749.13 1749.13 3570900
Nov 03, 2020 1631.78 1661.7 1616.62 1650.21 1650.21 1661700
Nov 02, 2020 1628.16 1660.77 1616.03 1626.03 1626.03 2535400
Oct 30, 2020 1672.11 1687 1604.46 1621.01 1621.01 4329100
Oct 29, 2020 1522.36 1593.71 1522.24 1567.24 1567.24 2003100
Oct 28, 2020 1559.74 1561.35 1514.62 1516.62 1516.62 1834000
Oct 27, 2020 1595.67 1606.84 1582.78 1604.26 1604.26 1229000
Oct 26, 2020 1625.01 1638.24 1576.5 1590.45 1590.45 1853300
Oct 23, 2020 1626.07 1642.36 1620.51 1641 1641 1375800
Oct 22, 2020 1593.05 1621.99 1585 1615.33 1615.33 1433600
Oct 21, 2020 1573.33 1618.73 1571.63 1593.31 1593.31 2568300
Oct 20, 2020 1527.05 1577.5 1525.67 1555.93 1555.93 2241700
Oct 19, 2020 1580.46 1588.15 1528 1534.61 1534.61 1607100
Oct 16, 2020 1565.85 1581.13 1563 1573.01 1573.01 1434700
Oct 15, 2020 1547.15 1575.1 1545.03 1559.13 1559.13 1540000
Oct 14, 2020 1578.59 1587.68 1550.53 1568.08 1568.08 1929300
Oct 13, 2020 1583.73 1590 1563.2 1571.68 1571.68 1601000
Oct 12, 2020 1543 1593.86 1532.57 1569.15 1569.15 2482600
Oct 09, 2020 1494.7 1516.52 1489.45 1515.22 1515.22 1435300
Oct 08, 2020 1465.09 1490 1465.09 1485.93 1485.93 1187800
Oct 07, 2020 1464.29 1468.96 1436 1460.29 1460.29 1746200
Oct 06, 2020 1475.58 1486.76 1448.59 1453.44 1453.44 1245400
Oct 05, 2020 1466.21 1488.21 1464.27 1486.02 1486.02 1113300
Oct 02, 2020 1462.03 1483.2 1450.92 1458.42 1458.42 1284100
Oct 01, 2020 1484.27 1499.04 1479.21 1490.09 1490.09 1779500
Sep 30, 2020 1466.8 1489.75 1459.88 1469.6 1469.6 1701600
Sep 29, 2020 1470.39 1476.66 1458.81 1469.33 1469.33 978200
Sep 28, 2020 1474.21 1476.8 1449.3 1464.52 1464.52 2007900
Sep 25, 2020 1432.63 1450 1413.34 1444.96 1444.96 1323000
Sep 24, 2020 1411.03 1443.71 1409.85 1428.29 1428.29 1450200
Sep 23, 2020 1458.78 1460.96 1407.7 1415.21 1415.21 1657400
Sep 22, 2020 1450.09 1469.52 1434.53 1465.46 1465.46 1583200
Sep 21, 2020 1440.06 1448.36 1406.55 1431.16 1431.16 2888800
Sep 18, 2020 1498.01 1503 1437.13 1459.99 1459.99 3103900
Sep 17, 2020 1496 1508.3 1470 1495.53 1495.53 1879800
Sep 16, 2020 1555.54 1562 1519.82 1520.9 1520.9 1311700
Sep 15, 2020 1536 1559.57 1531.83 1541.44 1541.44 1331100
Sep 14, 2020 1539.01 1564 1515.74 1519.28 1519.28 1696600
Sep 11, 2020 1536 1575.2 1497.36 1520.72 1520.72 1597100
Sep 10, 2020 1560.64 1584.08 1525.81 1532.02 1532.02 1618600
Sep 09, 2020 1557.53 1569 1536.05 1556.96 1556.96 1774700
Sep 08, 2020 1533.51 1563.86 1528.01 1532.39 1532.39 2610900
Sep 04, 2020 1624.26 1645.11 1547.61 1591.04 1591.04 2608600
Sep 03, 2020 1709.71 1709.71 1615.06 1641.84 1641.84 3107800
Sep 02, 2020 1673.78 1733.18 1666.33 1728.28 1728.28 2511200
Sep 01, 2020 1636.63 1665.73 1632.22 1660.71 1660.71 1825300
Aug 31, 2020 1647.89 1647.96 1630.31 1634.18 1634.18 1823400
Aug 28, 2020 1633.49 1647.17 1630.75 1644.41 1644.41 1499000
Aug 27, 2020 1653.68 1655 1625.75 1634.33 1634.33 1861600
Aug 26, 2020 1608 1659.22 1603.6 1652.38 1652.38 3993400
Aug 25, 2020 1582.07 1611.62 1582.07 1608.22 1608.22 2247100
Aug 24, 2020 1593.98 1614.17 1580.57 1588.2 1588.2 1409900
Aug 21, 2020 1577.03 1597.72 1568.01 1580.42 1580.42 1446500
Aug 20, 2020 1543.45 1585.87 1538.2 1581.75 1581.75 1706900
Aug 19, 2020 1553.31 1573.68 1543.95 1547.53 1547.53 1660600
Aug 18, 2020 1526.18 1562.47 1523.71 1558.6 1558.6 2027100
Aug 17, 2020 1514.67 1525.61 1507.97 1517.98 1517.98 1378300
Aug 14, 2020 1515.66 1521.9 1502.88 1507.73 1507.73 1354800
Aug 13, 2020 1510.34 1537.25 1508.01 1518.45 1518.45 1455200
Aug 12, 2020 1485.58 1512.39 1485.25 1506.62 1506.62 1437000
Aug 11, 2020 1492.44 1510 1478 1480.32 1480.32 1454400
Yahoo Finance 已停用其 API。试试这个 python library.
雅虎！财务略微改变了他们的结构。 现在需要 headers 用于 http 请求的数据检索。完成后效果很好。
对于 pandas 和 pandas-datareader，如果您使用它，您需要 升级 它们。 （已经排序）。可能在所有其他使用来自 yahoo!例如 backtrader 等，您需要在 yahoo! 上升级或添加 headers检索数据的脚本:).
pip install --upgrade pandas
pip install --upgrade pandas-datareader
祝你有愉快的一天 ;).
请将 pandas_datareader 升级到 >= 0.10.0 的版本。根据 release notes.
，此错误已在 0.10.0 中修复Fixed Yahoo readers which now require headers