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Yahoo Finance Data DL

  • Download historical data for analysis (raw)

Install deps

In [32]:
%pip install "yfinance[optional]"=="0.2.37"

Requirement already satisfied: yfinance==0.2.37 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from yfinance[optional]==0.2.37) (0.2.37)
Requirement already satisfied: pandas>=1.3.0 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from yfinance==0.2.37->yfinance[optional]==0.2.37) (2.2.1)
Requirement already satisfied: numpy>=1.16.5 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from yfinance==0.2.37->yfinance[optional]==0.2.37) (1.26.4)
Requirement already satisfied: requests>=2.31 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from yfinance==0.2.37->yfinance[optional]==0.2.37) (2.31.0)
Requirement already satisfied: multitasking>=0.0.7 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from yfinance==0.2.37->yfinance[optional]==0.2.37) (0.0.11)
Requirement already satisfied: lxml>=4.9.1 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from yfinance==0.2.37->yfinance[optional]==0.2.37) (5.1.0)
Requirement already satisfied: appdirs>=1.4.4 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from yfinance==0.2.37->yfinance[optional]==0.2.37) (1.4.4)
Requirement already satisfied: pytz>=2022.5 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from yfinance==0.2.37->yfinance[optional]==0.2.37) (2024.1)
Requirement already satisfied: frozendict>=2.3.4 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from yfinance==0.2.37->yfinance[optional]==0.2.37) (2.4.0)
Requirement already satisfied: peewee>=3.16.2 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from yfinance==0.2.37->yfinance[optional]==0.2.37) (3.17.1)
Requirement already satisfied: beautifulsoup4>=4.11.1 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from yfinance==0.2.37->yfinance[optional]==0.2.37) (4.12.3)
Requirement already satisfied: html5lib>=1.1 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from yfinance==0.2.37->yfinance[optional]==0.2.37) (1.1)
WARNING: yfinance 0.2.37 does not provide the extra 'optional'
Requirement already satisfied: soupsieve>1.2 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from beautifulsoup4>=4.11.1->yfinance==0.2.37->yfinance[optional]==0.2.37) (2.5)
Requirement already satisfied: six>=1.9 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from html5lib>=1.1->yfinance==0.2.37->yfinance[optional]==0.2.37) (1.16.0)
Requirement already satisfied: webencodings in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from html5lib>=1.1->yfinance==0.2.37->yfinance[optional]==0.2.37) (0.5.1)
Requirement already satisfied: python-dateutil>=2.8.2 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from pandas>=1.3.0->yfinance==0.2.37->yfinance[optional]==0.2.37) (2.9.0)
Requirement already satisfied: tzdata>=2022.7 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from pandas>=1.3.0->yfinance==0.2.37->yfinance[optional]==0.2.37) (2024.1)
Requirement already satisfied: charset-normalizer<4,>=2 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from requests>=2.31->yfinance==0.2.37->yfinance[optional]==0.2.37) (3.3.2)
Requirement already satisfied: idna<4,>=2.5 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from requests>=2.31->yfinance==0.2.37->yfinance[optional]==0.2.37) (3.6)
Requirement already satisfied: urllib3<3,>=1.21.1 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from requests>=2.31->yfinance==0.2.37->yfinance[optional]==0.2.37) (2.2.1)
Requirement already satisfied: certifi>=2017.4.17 in /home/marius/miniconda3/envs/lang_chain/lib/python3.11/site-packages (from requests>=2.31->yfinance==0.2.37->yfinance[optional]==0.2.37) (2024.2.2)
Note: you may need to restart the kernel to use updated packages.

DL

  • HG=F - Copper
In [33]:
import yfinance as yf

hg_f = yf.Ticker("HG=F")
In [34]:
# get all stock info
hg_f.info
Out[34]:
{'maxAge': 86400,
 'priceHint': 4,
 'previousClose': 3.926,
 'open': 3.9255,
 'dayLow': 3.8815,
 'dayHigh': 3.9465,
 'regularMarketPreviousClose': 3.926,
 'regularMarketOpen': 3.9255,
 'regularMarketDayLow': 3.8815,
 'regularMarketDayHigh': 3.9465,
 'volume': 80624,
 'regularMarketVolume': 80624,
 'averageVolume': 1088,
 'averageVolume10days': 4041,
 'averageDailyVolume10Day': 4041,
 'bid': 3.8905,
 'ask': 3.8915,
 'bidSize': 800,
 'askSize': 1200,
 'expireDate': 1716940800,
 'openInterest': 126184,
 'fiftyTwoWeekLow': 3.53,
 'fiftyTwoWeekHigh': 4.1895,
 'fiftyDayAverage': 3.81898,
 'twoHundredDayAverage': 3.7641976,
 'currency': 'USD',
 'exchange': 'CMX',
 'quoteType': 'FUTURE',
 'symbol': 'HGK24.CMX',
 'underlyingSymbol': 'HG=F',
 'shortName': 'Copper May 24',
 'firstTradeDateEpochUtc': 967608000,
 'timeZoneFullName': 'America/New_York',
 'timeZoneShortName': 'EST',
 'uuid': '02846b86-92eb-33ab-a801-f9b43107619f',
 'gmtOffSetMilliseconds': -18000000,
 'trailingPegRatio': None}
In [43]:
import pandas as pd
import numpy as np

# get historical market data
hist = hg_f.history(period="1y")

# Replace 0 values with NaN in specific columns
hist.replace({'Volume': {0: pd.NA}, 'Open': {0: pd.NA}}, inplace=True)
hist.replace(0, np.nan, inplace=True)  # Replace 0 with NaN

# Drop rows with NaN values in these specific columns
hist.dropna(subset=['Volume', 'Open'], inplace=True)

hist
Out[43]:
<style scoped=""> .dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; } </style>
Open High Low Close Volume Dividends Stock Splits
Date
2023-03-09 00:00:00-05:00 4.0465 4.0565 4.0300 4.0545 584 NaN NaN
2023-03-10 00:00:00-05:00 4.0120 4.0675 3.9900 4.0455 591 NaN NaN
2023-03-13 00:00:00-04:00 4.0230 4.0800 3.9460 4.0695 842 NaN NaN
2023-03-14 00:00:00-04:00 4.0395 4.0620 4.0010 4.0105 923 NaN NaN
2023-03-15 00:00:00-04:00 4.0210 4.0210 3.8565 3.8565 875 NaN NaN
... ... ... ... ... ... ... ...
2024-03-04 00:00:00-05:00 3.8450 3.8815 3.8435 3.8520 1136 NaN NaN
2024-03-05 00:00:00-05:00 3.8465 3.8630 3.8380 3.8440 929 NaN NaN
2024-03-06 00:00:00-05:00 3.8400 3.8915 3.8375 3.8705 987 NaN NaN
2024-03-07 00:00:00-05:00 3.8740 3.9310 3.8740 3.9195 1243 NaN NaN
2024-03-08 00:00:00-05:00 3.9175 3.9320 3.8780 3.8850 1243 NaN NaN

252 rows × 7 columns

In [45]:
import matplotlib.pyplot as plt
# Assuming 'data' is your DataFrame
plt.figure(figsize=(12, 5))



# Plotting Open
plt.subplot(1, 2, 2)
hist['Open'].hist(bins=20)
plt.title('Open Price Histogram')
plt.xlabel('Open Price')
plt.ylabel('Frequency')

plt.tight_layout()
plt.show()
No description has been provided for this image
In [48]:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt



# Plotting the 'Open' price as a line plot
plt.figure(figsize=(10, 6))
hist['Open'].plot(kind='line', title='Open Price Over Time', xlabel='Date', ylabel='Open Price')
plt.grid(True)
plt.show()
No description has been provided for this image
In [50]:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# Assuming 'hist' is your DataFrame with 'Date' set as the index and non-zero 'Open' values

# Calculate daily change in 'Open' prices
hist['OpenChange'] = hist['Open'].diff()

# Find points where the change in 'Open' price shifts direction
# This is a simple way to spot potential trend changes
trend_changes = hist['OpenChange'] * hist['OpenChange'].shift(-1) < 0

# Plotting the 'Open' price as a line plot
plt.figure(figsize=(10, 6))
hist['Open'].plot(kind='line', title='Open Price Over Time', xlabel='Date', ylabel='Open Price')
plt.grid(True)

# Marking trend changes
for date, change in trend_changes.items():
    if change:
        plt.plot(date, hist.loc[date, 'Open'], 'ro')  # Mark with red circle

plt.show()
No description has been provided for this image
In [30]:
# show meta information about the history (requires history() to be called first)
hg_f.history_metadata
Out[30]:
{'currency': 'USD',
 'symbol': 'HG=F',
 'exchangeName': 'CMX',
 'instrumentType': 'FUTURE',
 'firstTradeDate': 967608000,
 'regularMarketTime': 1709935198,
 'hasPrePostMarketData': False,
 'gmtoffset': -18000,
 'timezone': 'EST',
 'exchangeTimezoneName': 'America/New_York',
 'regularMarketPrice': 3.891,
 'chartPreviousClose': 4.042,
 'priceHint': 4,
 'currentTradingPeriod': {'pre': {'timezone': 'EST',
   'start': 1709874000,
   'end': 1709874000,
   'gmtoffset': -18000},
  'regular': {'timezone': 'EST',
   'start': 1709874000,
   'end': 1709960340,
   'gmtoffset': -18000},
  'post': {'timezone': 'EST',
   'start': 1709960340,
   'end': 1709960340,
   'gmtoffset': -18000}},
 'dataGranularity': '1d',
 'range': '1y',
 'validRanges': ['1d',
  '5d',
  '1mo',
  '3mo',
  '6mo',
  '1y',
  '2y',
  '5y',
  '10y',
  'ytd',
  'max']}
In [16]:
# show actions (dividends, splits, capital gains)
hg_f.actions
hg_f.dividends
hg_f.splits
hg_f.capital_gains  # only for mutual funds & etfs
Out[16]:
Series([], dtype: object)
In [18]:
# show share count
hg_f.get_shares_full(start="2022-01-01", end=None)
Out[18]:
yfinance.Ticker object <HG=F>
In [20]:
hg_f.income_stmt
hg_f.quarterly_income_stmt
Out[20]:
<style scoped=""> .dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; } </style>
In [21]:
# - balance sheet
hg_f.balance_sheet
hg_f.quarterly_balance_sheet
Out[21]:
<style scoped=""> .dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; } </style>
In [22]:
# - cash flow statement
hg_f.cashflow
hg_f.quarterly_cashflow
# see `Ticker.get_income_stmt()` for more options
Out[22]:
<style scoped=""> .dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; } </style>
In [23]:
# show holders
hg_f.major_holders
hg_f.institutional_holders
hg_f.mutualfund_holders
hg_f.insider_transactions
hg_f.insider_purchases
hg_f.insider_roster_holders

404 Client Error: Not Found for url: https://query2.finance.yahoo.com/v10/finance/quoteSummary/?modules=institutionOwnership%2CfundOwnership%2CmajorDirectHolders%2CmajorHoldersBreakdown%2CinsiderTransactions%2CinsiderHolders%2CnetSharePurchaseActivity&corsDomain=finance.yahoo.com&symbol=HG%3DF&formatted=false&crumb=kY9MYXZrrjV
Out[23]:
<style scoped=""> .dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; } </style>
In [24]:
# show recommendations
hg_f.recommendations
hg_f.recommendations_summary
hg_f.upgrades_downgrades

404 Client Error: Not Found for url: https://query2.finance.yahoo.com/v10/finance/quoteSummary/HG=F?modules=recommendationTrend&corsDomain=finance.yahoo.com&formatted=false&symbol=HG%3DF&crumb=kY9MYXZrrjV
404 Client Error: Not Found for url: https://query2.finance.yahoo.com/v10/finance/quoteSummary/HG=F?modules=upgradeDowngradeHistory&corsDomain=finance.yahoo.com&formatted=false&symbol=HG%3DF&crumb=kY9MYXZrrjV
Out[24]:
<style scoped=""> .dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; } </style>
In [25]:
# Show future and historic earnings dates, returns at most next 4 quarters and last 8 quarters by default. 
# Note: If more are needed use msft.get_earnings_dates(limit=XX) with increased limit argument.
hg_f.earnings_dates

HG=F: No earnings dates found, symbol may be delisted
In [26]:
# show ISIN code - *experimental*
# ISIN = International Securities Identification Number
hg_f.isin
Out[26]:
'-'
In [27]:
# show options expirations
hg_f.options
Out[27]:
()
In [28]:
# show news
hg_f.news
Out[28]:
[{'uuid': 'a081de49-3834-35d7-9b1a-49ae61a24622',
  'title': 'EMERGING MARKETS-Latam stocks advance, weak copper prices drag currencies of Chile, Peru',
  'publisher': 'Reuters',
  'link': 'https://finance.yahoo.com/news/emerging-markets-latam-stocks-advance-153434824.html',
  'providerPublishTime': 1706283274,
  'type': 'STORY',
  'relatedTickers': ['HG=F', '^BVSP', '^MXX']},
 {'uuid': '08c6cfc7-1146-374c-bf8f-8f02328cc4b1',
  'title': 'CANADA STOCKS-TSX futures edge up on higher gold prices; US data in focus',
  'publisher': 'Reuters',
  'link': 'https://finance.yahoo.com/news/canada-stocks-tsx-futures-edge-123846632.html',
  'providerPublishTime': 1706272726,
  'type': 'STORY',
  'relatedTickers': ['GC=F', 'ZG=F', 'HG=F', '^GSPC']},
 {'uuid': '1666725e-a880-3220-be81-4b39be02d706',
  'title': 'These Are the 4 Best Silver Coin Types To Buy in Order To Turn a Profit',
  'publisher': 'GOBankingRates',
  'link': 'https://finance.yahoo.com/news/4-best-silver-coin-types-123010528.html',
  'providerPublishTime': 1706272210,
  'type': 'STORY',
  'thumbnail': {'resolutions': [{'url': 'https://s.yimg.com/uu/api/res/1.2/BhiemWjsPOiPzWVgmzWacQ--~B/aD0xMDgwO3c9MTkyMDthcHBpZD15dGFjaHlvbg--/https://media.zenfs.com/en/gobankingrates_644/397831e32274b07c29579b8e42a54267',
     'width': 1920,
     'height': 1080,
     'tag': 'original'},
    {'url': 'https://s.yimg.com/uu/api/res/1.2/__z5WbG1O.bg53xqLE74Dg--~B/Zmk9ZmlsbDtoPTE0MDtweW9mZj0wO3c9MTQwO2FwcGlkPXl0YWNoeW9u/https://media.zenfs.com/en/gobankingrates_644/397831e32274b07c29579b8e42a54267',
     'width': 140,
     'height': 140,
     'tag': '140x140'}]},
  'relatedTickers': ['GC=F', 'ZG=F', 'HG=F', 'SI=F', 'ZI=F']},
 {'uuid': '0edc4734-fb05-3bb1-a95b-9e11c776fdc5',
  'title': 'Gold prices struggle before inflation, Fed cues; copper set for strong week',
  'publisher': 'Investing.com',
  'link': 'https://finance.yahoo.com/news/gold-prices-struggle-inflation-fed-001606596.html',
  'providerPublishTime': 1706228166,
  'type': 'STORY',
  'relatedTickers': ['HG=F', 'GC=F', 'ZG=F']},
 {'uuid': '7b91db52-a3f1-335d-9176-6d61187cf0a7',
  'title': 'Basic Materials Roundup: Market Talk',
  'publisher': 'The Wall Street Journal',
  'link': 'https://finance.yahoo.com/m/7b91db52-a3f1-335d-9176-6d61187cf0a7/basic-materials-roundup%3A.html',
  'providerPublishTime': 1706219880,
  'type': 'STORY',
  'thumbnail': {'resolutions': [{'url': 'https://s.yimg.com/uu/api/res/1.2/hus7PFWagBBSuGWsuAHBxA--~B/aD02NDA7dz0xMjgwO2FwcGlkPXl0YWNoeW9u/https://media.zenfs.com/en/wsj.com/7e9c00d68c1ab82df50577310bb19679',
     'width': 1280,
     'height': 640,
     'tag': 'original'},
    {'url': 'https://s.yimg.com/uu/api/res/1.2/2AS8Z8b8P15BKyqk61NEWQ--~B/Zmk9ZmlsbDtoPTE0MDtweW9mZj0wO3c9MTQwO2FwcGlkPXl0YWNoeW9u/https://media.zenfs.com/en/wsj.com/7e9c00d68c1ab82df50577310bb19679',
     'width': 140,
     'height': 140,
     'tag': '140x140'}]},
  'relatedTickers': ['GVDBF', 'GVDNY', 'GC=F', 'ZG=F', 'HG=F']},
 {'uuid': '2ce9d404-879c-3b5c-85c2-652c92639df1',
  'title': 'Closing prices for crude oil, gold and other commodities',
  'publisher': 'Associated Press Finance',
  'link': 'https://finance.yahoo.com/news/closing-prices-crude-oil-gold-201521282.html',
  'providerPublishTime': 1706213721,
  'type': 'STORY',
  'relatedTickers': ['CL=F',
   'SI=F',
   'ZI=F',
   'NG=F',
   'GC=F',
   'ZG=F',
   'HG=F',
   'HO=F']},
 {'uuid': 'e0748b77-83b7-34c3-b83e-f55508291594',
  'title': 'Crypto for Advisors: Unlocking Crypto Custody',
  'publisher': 'CoinDesk',
  'link': 'https://finance.yahoo.com/m/e0748b77-83b7-34c3-b83e-f55508291594/crypto-for-advisors%3A.html',
  'providerPublishTime': 1706199734,
  'type': 'STORY',
  'thumbnail': {'resolutions': [{'url': 'https://s.yimg.com/uu/api/res/1.2/YvjxRlrTdjUCMJlc1MT4tg--~B/aD0zMDAwO3c9NDUwMDthcHBpZD15dGFjaHlvbg--/https://media.zenfs.com/en/coindesk_75/c7a00a6fe2bc93bfbbac3e92d2fac0e6',
     'width': 4500,
     'height': 3000,
     'tag': 'original'},
    {'url': 'https://s.yimg.com/uu/api/res/1.2/q.NOd5AdTb2Y1wpOwX9L.w--~B/Zmk9ZmlsbDtoPTE0MDtweW9mZj0wO3c9MTQwO2FwcGlkPXl0YWNoeW9u/https://media.zenfs.com/en/coindesk_75/c7a00a6fe2bc93bfbbac3e92d2fac0e6',
     'width': 140,
     'height': 140,
     'tag': '140x140'}]},
  'relatedTickers': ['HG=F']},
 {'uuid': '922264e0-c1d2-3af4-9d38-c318b8a7b523',
  'title': "Blinken hails progress in construction of Angola's Lobito rail corridor",
  'publisher': 'Reuters',
  'link': 'https://finance.yahoo.com/news/blinken-hails-progress-construction-angolas-155740812.html',
  'providerPublishTime': 1706198260,
  'type': 'STORY',
  'relatedTickers': ['HG=F']}]
In [29]:
# get option chain for specific expiration
opt = hg_f.option_chain('2024-06-21')
# data available via: opt.calls, opt.puts

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[29], line 2
      1 # get option chain for specific expiration
----> 2 opt = hg_f.option_chain('2024-06-21')
      3 # data available via: opt.calls, opt.puts

File ~/miniconda3/envs/lang_chain/lib/python3.11/site-packages/yfinance/ticker.py:91, in Ticker.option_chain(self, date, tz)
     89     self._download_options()
     90 if date not in self._expirations:
---> 91     raise ValueError(
     92         f"Expiration `{date}` cannot be found. "
     93         f"Available expirations are: [{', '.join(self._expirations)}]")
     94 date = self._expirations[date]
     95 options = self._download_options(date)

ValueError: Expiration `2024-06-21` cannot be found. Available expirations are: []
In [ ]:
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