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"%pip install \"yfinance[optional]\"==\"0.2.37\""
]
},
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"source": [
"import yfinance as yf\n",
"\n",
"hg_f = yf.Ticker(\"HG=F\")"
]
},
{
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"id": "f8531df814e529fb",
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"source": [
"import pandas as pd\n",
"import numpy as np\n",
"\n",
"# get historical market data\n",
"hist = hg_f.history(period=\"100y\")\n",
"\n",
"# Replace 0 values with NaN in specific columns\n",
"hist.replace({'Volume': {0: pd.NA}, 'Open': {0: pd.NA}}, inplace=True)\n",
"hist.replace(0, np.nan, inplace=True) # Replace 0 with NaN\n",
"\n",
"columns = ['Open', 'High', 'Low', 'Close', 'Volume']"
]
},
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" Open High Low Close Volume Dividends \\\n",
"Date \n",
"2000-08-30 00:00:00-04:00 0.879 0.887 0.8770 0.8850 2886 NaN \n",
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"2000-09-06 00:00:00-04:00 0.905 0.906 0.8975 0.9015 1195 NaN \n",
"\n",
" Stock Splits \n",
"Date \n",
"2000-08-30 00:00:00-04:00 NaN \n",
"2000-08-31 00:00:00-04:00 NaN \n",
"2000-09-01 00:00:00-04:00 NaN \n",
"2000-09-05 00:00:00-04:00 NaN \n",
"2000-09-06 00:00:00-04:00 NaN "
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"hist.head()"
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" Open High Low Close Volume Dividends Stock Splits\n",
"2000-08-30 0.879 0.887 0.8770 0.8850 2886 NaN NaN\n",
"2000-08-31 0.885 0.888 0.8800 0.8850 1095 NaN NaN\n",
"2000-09-01 0.878 0.889 0.8780 0.8890 3449 NaN NaN\n",
"2000-09-05 0.896 0.907 0.8950 0.9060 1397 NaN NaN\n",
"2000-09-06 0.905 0.906 0.8975 0.9015 1195 NaN NaN"
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"# Convert the index to datetime if it's not already\n",
"hist.index = pd.to_datetime(hist.index)\n",
"\n",
"# Strip the time and timezone, keeping only the date for the index\n",
"hist.index = hist.index.date\n",
"\n",
"hist.head()"
]
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"from datetime import datetime\n",
"\n",
"# Get the current date in 'YYYY-MM-DD' format\n",
"current_date = datetime.now().strftime('%Y-%m-%d')\n",
"\n",
"# Create the file name with the current date\n",
"file_name = f'./Data_COPPER_{current_date}.csv'\n",
"\n",
"hist = hist.round(3)\n",
"\n",
"# Save the DataFrame to CSV with the dynamic file name\n",
"hist[[\"Open\", \"High\", \"Low\", \"Close\"]].to_csv(file_name)"
]
},
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