trading_analysis/Yahoo_Finance_DL_COPPER_EXCEL.ipynb

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{
"cells": [
{
"cell_type": "code",
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"id": "initial_id",
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"source": [
"%pip install \"yfinance[optional]\"==\"0.2.37\""
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "904104edfdda9e89",
"metadata": {
"ExecuteTime": {
"end_time": "2024-03-15T12:53:50.140736Z",
"start_time": "2024-03-15T12:53:49.262218Z"
},
"collapsed": false
},
"outputs": [],
"source": [
"import yfinance as yf\n",
"\n",
"hg_f = yf.Ticker(\"HG=F\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "f8531df814e529fb",
"metadata": {
"ExecuteTime": {
"end_time": "2024-03-15T12:59:52.590852Z",
"start_time": "2024-03-15T12:59:52.243074Z"
},
"collapsed": false
},
"outputs": [],
"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']\n",
"\n",
"hist.to_csv(f'./Data_COPPER.csv')"
]
},
{
"cell_type": "code",
"id": "de2634931db1a5d6",
"metadata": {
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}
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"display_name": "Python 3",
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"language_info": {
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