{ "cells": [ { "cell_type": "code", "execution_count": 43, "id": "1e66f664", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[**********************67%******* ] 10 of 15 completed$AKERBP.OL: possibly delisted; no price data found (period=5y) (Yahoo error = \"No data found, symbol may be delisted\")\n", "[**********************80%************* ] 12 of 15 completed$REC.OL: possibly delisted; no price data found (period=5y) (Yahoo error = \"No data found, symbol may be delisted\")\n", "[**********************87%***************** ] 13 of 15 completed$NODL.OL: possibly delisted; no price data found (period=5y) (Yahoo error = \"No data found, symbol may be delisted\")\n", "[*********************100%***********************] 15 of 15 completed\n", "\n", "3 Failed downloads:\n", "['AKERBP.OL', 'REC.OL', 'NODL.OL']: possibly delisted; no price data found (period=5y) (Yahoo error = \"No data found, symbol may be delisted\")\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Date\n", "2021-06-30 134.384613\n", "2021-07-01 136.464767\n", "2021-07-02 136.036942\n", "2021-07-05 136.022202\n", "2021-07-06 134.989517\n", " ... \n", "2026-06-24 311.100006\n", "2026-06-25 308.799988\n", "2026-06-26 309.100006\n", "2026-06-29 311.000000\n", "2026-06-30 313.500000\n", "Name: EQNR.OL, Length: 1257, dtype: float64\n" ] } ], "source": [ "import yfinance as yf\n", "import pandas as pd\n", "\n", "tickere_OSEBX = [\"EQNR.OL\", \"YAR.OL\", \"NHY.OL\", \"ELK.OL\", \"MOWI.OL\", \"DNB.OL\", \"AKERBP.OL\", \"KOG.OL\", \"NODL.OL\", \"REC.OL\", \"TOM.OL\", \"SALM.OL\", \"STB.OL\", \"SUBC.OL\", \"TEL.OL\"] #velg tickere du vil se på Oslo Børs\n", "data = yf.download(tickere_OSEBX, period=\"5y\")[\"Close\"] #bruk funbksjonen til yfinance, og hent lengden på perioden til dataene\n", "print(data[\"EQNR.OL\"])\n" ] }, { "cell_type": "code", "execution_count": 45, "id": "42f0174d", "metadata": {}, "outputs": [], "source": [ "resultater = {} #opprett en tom dictionary for å lagre resultatene\n", "\n", "for ticker in tickere_OSEBX:\n", " if ticker not in data.columns:\n", " continue\n", " df = data[[ticker]].copy()\n", " df.columns = [\"Kurs\"]\n", " df[\"GJ50\"] = df[\"Kurs\"].rolling(window=50).mean() # Beregn glidende gjennomsnitt for 50 dager\n", " df[\"GJ200\"] = df[\"Kurs\"].rolling(window=200).mean() # Beregn glidende gjennomsnitt for 200 dager\n", "\n", " resultater[ticker] = df \n" ] }, { "cell_type": "code", "execution_count": 49, "id": "d9546709", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Kurs GJ50 GJ200\n", "Date \n", "2021-06-30 313.397217 NaN NaN\n", "2021-07-01 317.269684 NaN NaN\n", "2021-07-02 319.413391 NaN NaN\n", "2021-07-05 323.770020 NaN NaN\n", "2021-07-06 320.865570 NaN NaN\n", "... ... ... ...\n", "2026-06-24 441.000000 500.536213 427.910471\n", "2026-06-25 430.000000 498.198028 428.333996\n", "2026-06-26 437.200012 496.533297 428.801672\n", "2026-06-29 431.899994 494.601427 429.235176\n", "2026-06-30 435.399994 492.624459 429.678506\n", "\n", "[1257 rows x 3 columns]\n" ] } ], "source": [ "print(resultater[\"YAR.OL\"]) " ] }, { "cell_type": "code", "execution_count": 50, "id": "5121714a", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "hovertemplate": "variable=Kurs
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"gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" } }, "shapedefaults": { "line": { "color": "#2a3f5f" } }, "ternary": { "aaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "baxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "caxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "title": { "text": "Kurs og glidende gjennomsnitt" }, "xaxis": { "anchor": "y", "domain": [ 0, 1 ], "title": { "text": "Date" } }, "yaxis": { "anchor": "x", "domain": [ 0, 1 ], "title": { "text": "value" } } } } }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import plotly.express as px\n", "\n", "fig = px.line(\n", " resultater[\"YAR.OL\"], #NB: velg ticker for selskapet du vil se på\n", " y=[\"Kurs\", \"GJ50\", \"GJ200\"],\n", " title=\"Kurs og glidende gjennomsnitt\"\n", ") #opprett graf\n", "fig.show()" ] }, { "cell_type": "code", "execution_count": null, "id": "45b1b68b", "metadata": {}, "outputs": [], "source": [ "with pd.ExcelWriter(\"gg_oslo_bors_analyse.xlsx\", engine=\"openpyxl\") as writer:\n", " for ticker, df in resultater.items():\n", " df.to_excel(writer, sheet_name=ticker)\n", "\n", "#Skriv ut i excel om ønskelig \n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.13.14" } }, "nbformat": 4, "nbformat_minor": 5 }