diff --git a/testing.ipynb b/testing.ipynb deleted file mode 100644 index b0a5121..0000000 --- a/testing.ipynb +++ /dev/null @@ -1,423 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "3f7938c0-98e3-43b8-86e8-4f000cda7ce5", - "metadata": {}, - "outputs": [], - "source": [ - "import datetime\n", - "import pandas as pd\n", - "\n", - "from fincal.fincal import TimeSeries\n", - "from fincal.core import Series" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "4b8ccd5f-dfff-4202-82c4-f66a30c122b6", - "metadata": {}, - "outputs": [], - "source": [ - "dfd = pd.read_csv('test_files/nav_history_daily - copy.csv')\n", - "\n", - "dfd = dfd[dfd['amfi_code'] == 118825].reset_index(drop=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "c52b0c2c-dd01-48dd-9ffa-3147ec9571ef", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Warning: The input data contains duplicate dates which have been ignored.\n" - ] - }, - { - "data": { - "text/plain": [ - "TimeSeries([(datetime.datetime(2013, 1, 2, 0, 0), 18.972),\n", - "\t (datetime.datetime(2013, 1, 3, 0, 0), 19.011),\n", - "\t (datetime.datetime(2013, 1, 4, 0, 0), 19.008)\n", - "\t ...\n", - "\t (datetime.datetime(2022, 2, 10, 0, 0), 86.5),\n", - "\t (datetime.datetime(2022, 2, 11, 0, 0), 85.226),\n", - "\t (datetime.datetime(2022, 2, 14, 0, 0), 82.533)], frequency='D')" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ts = TimeSeries([(i.date, i.nav) for i in dfd.itertuples()], frequency='D')\n", - "\n", - "ts" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "9e8ff6c6-3a36-435a-ba87-5b9844c18779", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[(datetime.datetime(2021, 1, 1, 0, 0), 66.652),\n", - " (datetime.datetime(2020, 1, 1, 0, 0), 57.804)]" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ts[['2021-01-01', '2020-01-01']]" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "4d927a61-0f90-4b47-89b7-0e0d3ab1b442", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Series([False, False, False, False, False, False, False, False, False, False])" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "s = ts.dates > '2020-01-01'\n", - "s[:10]" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "311d1c07-d827-4d69-855f-883e1198c162", - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "bb625050-5d7b-45a9-9cde-ac6e599adea5", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0 False\n", - "1 False\n", - "2 False\n", - "3 False\n", - "4 False\n", - " ... \n", - "2196 True\n", - "2197 True\n", - "2198 True\n", - "2199 True\n", - "2200 True\n", - "Length: 2201, dtype: bool" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pd.Series(s)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "dc469722-c816-4b57-8d91-7a3b865f86be", - "metadata": { - "scrolled": true, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Wall time: 14 ms\n" - ] - }, - { - "data": { - "text/plain": [ - "[(datetime.datetime(2020, 1, 1, 0, 0), 0.13778442642311628),\n", - " (datetime.datetime(2020, 1, 2, 0, 0), 0.15907011891977874),\n", - " (datetime.datetime(2020, 1, 3, 0, 0), 0.16528842679940592),\n", - " (datetime.datetime(2020, 1, 6, 0, 0), 0.13725881835976517),\n", - " (datetime.datetime(2020, 1, 7, 0, 0), 0.1361567661029075),\n", - " (datetime.datetime(2020, 1, 8, 0, 0), 0.12943599493029145),\n", - " (datetime.datetime(2020, 1, 9, 0, 0), 0.14162066246056781),\n", - " (datetime.datetime(2020, 1, 10, 0, 0), 0.14866092589666624),\n", - " (datetime.datetime(2020, 1, 13, 0, 0), 0.15898777321998292),\n", - 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"# print(ts.calculate_returns(to_date, years=7))\n", - "ts.calculate_rolling_returns(from_date, to_date)" - ] - } - ], - "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": "3.9.2" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -}