diff --git a/testing.ipynb b/testing.ipynb index 3842ef0..51311f3 100644 --- a/testing.ipynb +++ b/testing.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "id": "3f7938c0-98e3-43b8-86e8-4f000cda7ce5", "metadata": {}, "outputs": [], @@ -16,160 +16,107 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "id": "4b8ccd5f-dfff-4202-82c4-f66a30c122b6", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[(datetime.datetime(2022, 1, 31, 0, 0), 310.980011),\n", + " (datetime.datetime(2021, 5, 28, 0, 0), 249.679993)]" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "dfd = pd.read_csv('test_files/nav_history_daily - copy.csv')\n", - "dfd = dfd[dfd['amfi_code'] == 118825].reset_index(drop=True)" + "dfd = pd.read_csv('test_files/msft.csv')\n", + "# dfd = dfd[dfd['amfi_code'] == 118825].reset_index(drop=True)\n", + "ts = TimeSeries([(i.date, i.nav) for i in dfd.itertuples()], frequency='D')\n", + "repr(ts)\n", + "ts[['2022-01-31', '2021-05-28']]" ] }, { "cell_type": "code", - "execution_count": 12, - "id": "c52b0c2c-dd01-48dd-9ffa-3147ec9571ef", + "execution_count": 3, + "id": "086d4377-d1b1-4e51-84c0-39dee28ef75e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Warning: The input data contains duplicate dates which have been ignored.\n" + "Wall time: 17 ms\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", + "TimeSeries([(datetime.datetime(2022, 1, 3, 0, 0), 334.75),\n", + "\t (datetime.datetime(2022, 1, 4, 0, 0), 329.01001),\n", + "\t (datetime.datetime(2022, 1, 5, 0, 0), 316.380005)\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), 82.53299999999999)], frequency='D')" + "\t (datetime.datetime(2022, 2, 16, 0, 0), 299.5),\n", + "\t (datetime.datetime(2022, 2, 17, 0, 0), 290.730011),\n", + "\t (datetime.datetime(2022, 2, 18, 0, 0), 287.929993)], frequency='D')" ] }, - "execution_count": 12, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "ts = TimeSeries([(i.date, i.nav) for i in dfd.itertuples()], frequency='D')\n", - "ts" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "9e8ff6c6-3a36-435a-ba87-5b9844c18779", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[(datetime.datetime(2022, 1, 31, 0, 0), 85.18),\n", - " (datetime.datetime(2021, 5, 31, 0, 0), 74.85)]" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ts[['2022-01-31', '2021-05-31']]" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "086d4377-d1b1-4e51-84c0-39dee28ef75e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "TimeSeries([(datetime.datetime(2021, 2, 15, 0, 0), 73.483),\n", - "\t (datetime.datetime(2021, 2, 16, 0, 0), 73.237),\n", - "\t (datetime.datetime(2021, 2, 17, 0, 0), 72.98)\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), 82.53299999999999)], frequency='D')" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ts[ts.dates>'2021-02-14']" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "6f1226a3-2327-435b-88e7-fd0fdcc8cc1c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "TimeSeries([(datetime.datetime(2020, 1, 2, 0, 0), 58.285),\n", - "\t (datetime.datetime(2020, 1, 3, 0, 0), 58.056999999999995),\n", - "\t (datetime.datetime(2020, 1, 6, 0, 0), 56.938)\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), 82.53299999999999)], frequency='D')" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "s = ts.dates > '2020-01-01'\n", + "%%time\n", + "s = ts.dates >= '2022-01-01'\n", "ts[s]" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 4, "id": "e815edc9-3746-4192-814e-bd27b2771a0c", "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Wall time: 5.97 ms\n" + ] + }, { "data": { "text/plain": [ - "[(datetime.datetime(2013, 1, 2, 0, 0), 18.972),\n", - " (datetime.datetime(2013, 1, 3, 0, 0), 19.011),\n", - " (datetime.datetime(2013, 1, 4, 0, 0), 19.008),\n", - " (datetime.datetime(2013, 1, 7, 0, 0), 18.95),\n", - " (datetime.datetime(2013, 1, 8, 0, 0), 18.954),\n", - " (datetime.datetime(2013, 1, 9, 0, 0), 18.94),\n", - " (datetime.datetime(2013, 1, 10, 0, 0), 18.957),\n", - " (datetime.datetime(2013, 1, 11, 0, 0), 18.948),\n", - " (datetime.datetime(2013, 1, 14, 0, 0), 19.177),\n", - " (datetime.datetime(2013, 1, 15, 0, 0), 19.272000000000002)]" + "[(datetime.datetime(1992, 2, 19, 0, 0), 2.398438),\n", + " (datetime.datetime(1992, 2, 20, 0, 0), 2.447917),\n", + " (datetime.datetime(1992, 2, 21, 0, 0), 2.385417),\n", + " (datetime.datetime(1992, 2, 24, 0, 0), 2.393229),\n", + " (datetime.datetime(1992, 2, 25, 0, 0), 2.411458),\n", + " (datetime.datetime(1992, 2, 26, 0, 0), 2.541667),\n", + " (datetime.datetime(1992, 2, 27, 0, 0), 2.601563),\n", + " (datetime.datetime(1992, 2, 28, 0, 0), 2.572917),\n", + " (datetime.datetime(1992, 3, 2, 0, 0), 2.5625),\n", + " (datetime.datetime(1992, 3, 3, 0, 0), 2.567708)]" ] }, - "execution_count": 10, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "%%time\n", "ts.iloc[:10]" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 5, "id": "dc469722-c816-4b57-8d91-7a3b865f86be", "metadata": { "tags": [] @@ -179,26 +126,66 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: total: 15.6 ms\n", - "Wall time: 10 ms\n" + "Wall time: 311 ms\n" ] } ], "source": [ "%%time\n", - "from_date = datetime.date(2020, 1, 1)\n", - "to_date = datetime.date(2021, 1, 1)\n", + "from_date = datetime.date(1994, 1, 1)\n", + "to_date = datetime.date(2022, 1, 1)\n", "# print(ts.calculate_returns(to_date, years=7))\n", "rr = ts.calculate_rolling_returns(from_date, to_date)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "e5d357b4-4fe5-4a0a-8107-0ab6828d7c41", "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "TimeSeries([(datetime.datetime(1994, 1, 3, 0, 0), -0.06149359306648605),\n", + "\t (datetime.datetime(1994, 1, 4, 0, 0), -0.05433177603118022),\n", + "\t (datetime.datetime(1994, 1, 5, 0, 0), -0.04913276300578029)\n", + "\t ...\n", + "\t (datetime.datetime(2021, 12, 29, 0, 0), 0.5255410267822715),\n", + "\t (datetime.datetime(2021, 12, 30, 0, 0), 0.5306749265370103),\n", + "\t (datetime.datetime(2021, 12, 31, 0, 0), 0.5120942811985818)], frequency='D')" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "rr" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "4bad2efa", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Series([1.0, 2.0, 3.0, 4.0, 5.0])" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sr = Series([1, 2, 3, 4, 5], 'number')\n", + "sr" + ] } ], "metadata": { @@ -217,7 +204,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.3" + "version": "3.9.2" } }, "nbformat": 4,