mirror of
https://github.com/Magnus167/msyrs.git
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python working with notebook!
This commit is contained in:
Palash Tyagi
364
notebooks/python-notebook.ipynb
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364
notebooks/python-notebook.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Build and install the package\n",
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"\n",
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"```bash\n",
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"python -m venv .venv\n",
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"\n",
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"# source .venv/bin/activate\n",
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"./.venv/Scripts/activate\n",
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"\n",
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"pip install maturin\n",
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"\n",
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"maturin develop --release\n",
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"```"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"e:\\Work\\ruzt\\msyrs\\.venv\\Lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
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" from .autonotebook import tqdm as notebook_tqdm\n"
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]
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}
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],
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"source": [
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"import macrosynergy\n",
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"import pandas as pd\n",
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"import numpy as np\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"import msyrs\n",
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"import polars as pl"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"DATA_FOLDER_PATH = \"E:/Work/jpmaqs-data\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div><style>\n",
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".dataframe > thead > tr,\n",
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".dataframe > tbody > tr {\n",
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" text-align: right;\n",
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" white-space: pre-wrap;\n",
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"}\n",
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"</style>\n",
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"<small>shape: (5, 7)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>real_date</th><th>cid</th><th>xcat</th><th>value</th><th>grading</th><th>eop_lag</th><th>mop_lag</th></tr><tr><td>date</td><td>str</td><td>str</td><td>f64</td><td>f64</td><td>i64</td><td>i64</td></tr></thead><tbody><tr><td>2010-03-03</td><td>"USD"</td><td>"ADPEMPL_SA_P1M1ML1"</td><td>-0.173806</td><td>3.0</td><td>3</td><td>33</td></tr><tr><td>2010-03-04</td><td>"USD"</td><td>"ADPEMPL_SA_P1M1ML1"</td><td>-0.173806</td><td>3.0</td><td>4</td><td>34</td></tr><tr><td>2010-03-05</td><td>"USD"</td><td>"ADPEMPL_SA_P1M1ML1"</td><td>-0.173806</td><td>3.0</td><td>5</td><td>35</td></tr><tr><td>2010-03-08</td><td>"USD"</td><td>"ADPEMPL_SA_P1M1ML1"</td><td>-0.173806</td><td>3.0</td><td>8</td><td>38</td></tr><tr><td>2010-03-09</td><td>"USD"</td><td>"ADPEMPL_SA_P1M1ML1"</td><td>-0.173806</td><td>3.0</td><td>9</td><td>39</td></tr></tbody></table></div>"
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],
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"text/plain": [
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"shape: (5, 7)\n",
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"┌────────────┬─────┬────────────────────┬───────────┬─────────┬─────────┬─────────┐\n",
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"│ real_date ┆ cid ┆ xcat ┆ value ┆ grading ┆ eop_lag ┆ mop_lag │\n",
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"│ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n",
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"│ date ┆ str ┆ str ┆ f64 ┆ f64 ┆ i64 ┆ i64 │\n",
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"╞════════════╪═════╪════════════════════╪═══════════╪═════════╪═════════╪═════════╡\n",
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"│ 2010-03-03 ┆ USD ┆ ADPEMPL_SA_P1M1ML1 ┆ -0.173806 ┆ 3.0 ┆ 3 ┆ 33 │\n",
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"│ 2010-03-04 ┆ USD ┆ ADPEMPL_SA_P1M1ML1 ┆ -0.173806 ┆ 3.0 ┆ 4 ┆ 34 │\n",
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"│ 2010-03-05 ┆ USD ┆ ADPEMPL_SA_P1M1ML1 ┆ -0.173806 ┆ 3.0 ┆ 5 ┆ 35 │\n",
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"│ 2010-03-08 ┆ USD ┆ ADPEMPL_SA_P1M1ML1 ┆ -0.173806 ┆ 3.0 ┆ 8 ┆ 38 │\n",
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"│ 2010-03-09 ┆ USD ┆ ADPEMPL_SA_P1M1ML1 ┆ -0.173806 ┆ 3.0 ┆ 9 ┆ 39 │\n",
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"└────────────┴─────┴────────────────────┴───────────┴─────────┴─────────┴─────────┘"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"dfpath = f\"{DATA_FOLDER_PATH}/data/ADPEMPL_SA_P1M1ML1/USD_ADPEMPL_SA_P1M1ML1.csv\"\n",
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"\n",
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"\n",
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"ldf: pl.DataFrame = msyrs.qdf.load_qdf(dfpath)\n",
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"ldf.head(5)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"cids_dm = \"AUD.CAD.CHF.EUR.GBP.JPY.NOK.NZD.SEK.USD\".split(\".\")\n",
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"cids_em = \"CLP.COP.CZK.HUF.IDR.ILS.INR.KRW.MXN.PLN.THB.TRY.TWD.ZAR\".split(\".\")\n",
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"cids = cids_dm + cids_em\n",
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"cids_dux = list(set(cids) - set([\"IDR\", \"NZD\"]))\n",
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"ecos = \"CPIC_SA_P1M1ML12.CPIC_SJA_P3M3ML3AR.CPIC_SJA_P6M6ML6AR.CPIH_SA_P1M1ML12.CPIH_SJA_P3M3ML3AR.CPIH_SJA_P6M6ML6AR.INFTEFF_NSA.INTRGDP_NSA_P1M1ML12_3MMA.INTRGDPv5Y_NSA_P1M1ML12_3MMA.PCREDITGDP_SJA_D1M1ML12.RGDP_SA_P1Q1QL4_20QMA.RYLDIRS02Y_NSA.RYLDIRS05Y_NSA.PCREDITBN_SJA_P1M1ML12\".split(\n",
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" \".\"\n",
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")\n",
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"[\"CPIC\", \"CPIH\", \"INFTEFF\", \"INTRGDP\", \"INTRGDPv5Y\", \"PCREDITGDP\", \"RGDP\", \"RYLDIRS\", \"PCREDITBN\"]\n",
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"[\"\"]\n",
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"\n",
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"mkts = \"DU02YXR_NSA.DU05YXR_NSA.DU02YXR_VT10.DU05YXR_VT10.EQXR_NSA.EQXR_VT10.FXXR_NSA.FXXR_VT10.FXCRR_NSA.FXTARGETED_NSA.FXUNTRADABLE_NSA\".split(\n",
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" \".\"\n",
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")\n",
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"xcats = ecos + mkts\n",
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"\n",
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"tickers = [f\"{c}_{x}\" for c in cids for x in xcats]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div><style>\n",
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".dataframe > thead > tr,\n",
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".dataframe > tbody > tr {\n",
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" text-align: right;\n",
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" white-space: pre-wrap;\n",
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"}\n",
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"</style>\n",
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"<small>shape: (5, 7)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>real_date</th><th>cid</th><th>xcat</th><th>value</th><th>grading</th><th>eop_lag</th><th>mop_lag</th></tr><tr><td>date</td><td>str</td><td>str</td><td>f64</td><td>f64</td><td>i64</td><td>i64</td></tr></thead><tbody><tr><td>1990-04-26</td><td>"AUD"</td><td>"CPIC_SA_P1M1ML12"</td><td>6.434599</td><td>2.0</td><td>26</td><td>223</td></tr><tr><td>1990-04-27</td><td>"AUD"</td><td>"CPIC_SA_P1M1ML12"</td><td>6.434599</td><td>2.0</td><td>27</td><td>224</td></tr><tr><td>1990-04-30</td><td>"AUD"</td><td>"CPIC_SA_P1M1ML12"</td><td>6.434599</td><td>2.0</td><td>30</td><td>227</td></tr><tr><td>1990-05-01</td><td>"AUD"</td><td>"CPIC_SA_P1M1ML12"</td><td>6.434599</td><td>2.0</td><td>31</td><td>228</td></tr><tr><td>1990-05-02</td><td>"AUD"</td><td>"CPIC_SA_P1M1ML12"</td><td>6.434599</td><td>2.0</td><td>32</td><td>229</td></tr></tbody></table></div>"
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],
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"text/plain": [
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"shape: (5, 7)\n",
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"┌────────────┬─────┬──────────────────┬──────────┬─────────┬─────────┬─────────┐\n",
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"│ real_date ┆ cid ┆ xcat ┆ value ┆ grading ┆ eop_lag ┆ mop_lag │\n",
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"│ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n",
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"│ date ┆ str ┆ str ┆ f64 ┆ f64 ┆ i64 ┆ i64 │\n",
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"╞════════════╪═════╪══════════════════╪══════════╪═════════╪═════════╪═════════╡\n",
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"│ 1990-04-26 ┆ AUD ┆ CPIC_SA_P1M1ML12 ┆ 6.434599 ┆ 2.0 ┆ 26 ┆ 223 │\n",
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"│ 1990-04-27 ┆ AUD ┆ CPIC_SA_P1M1ML12 ┆ 6.434599 ┆ 2.0 ┆ 27 ┆ 224 │\n",
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"│ 1990-04-30 ┆ AUD ┆ CPIC_SA_P1M1ML12 ┆ 6.434599 ┆ 2.0 ┆ 30 ┆ 227 │\n",
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"│ 1990-05-01 ┆ AUD ┆ CPIC_SA_P1M1ML12 ┆ 6.434599 ┆ 2.0 ┆ 31 ┆ 228 │\n",
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"│ 1990-05-02 ┆ AUD ┆ CPIC_SA_P1M1ML12 ┆ 6.434599 ┆ 2.0 ┆ 32 ┆ 229 │\n",
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"└────────────┴─────┴──────────────────┴──────────┴─────────┴─────────┴─────────┘"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"big_df: pl.DataFrame = msyrs.qdf.load_qdf_from_download_bank(\n",
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" folder_path=DATA_FOLDER_PATH, tickers=tickers\n",
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")\n",
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"big_df.head(5)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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"sel_cids = [\"USD\", \"EUR\", \"GBP\", \"AUD\", \"CAD\"]\n",
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"start = \"2024-11-14\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
|
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"<div><style>\n",
|
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".dataframe > thead > tr,\n",
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".dataframe > tbody > tr {\n",
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" text-align: right;\n",
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" white-space: pre-wrap;\n",
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"}\n",
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"</style>\n",
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"<small>shape: (20, 7)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>real_date</th><th>cid</th><th>xcat</th><th>value</th><th>grading</th><th>eop_lag</th><th>mop_lag</th></tr><tr><td>date</td><td>str</td><td>str</td><td>f64</td><td>f64</td><td>i64</td><td>i64</td></tr></thead><tbody><tr><td>2024-11-14</td><td>"AUD"</td><td>"EQXR_NSA"</td><td>0.329188</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>"AUD"</td><td>"EQXR_NSA"</td><td>0.826346</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>"CAD"</td><td>"EQXR_NSA"</td><td>0.199402</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>"CAD"</td><td>"EQXR_NSA"</td><td>-0.696517</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>"EUR"</td><td>"EQXR_NSA"</td><td>2.024889</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>…</td><td>…</td><td>…</td><td>…</td><td>…</td><td>…</td><td>…</td></tr><tr><td>2024-11-15</td><td>"EUR"</td><td>"EQXR_VT10"</td><td>-0.477901</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>"GBP"</td><td>"EQXR_VT10"</td><td>0.664208</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>"GBP"</td><td>"EQXR_VT10"</td><td>-0.068778</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>"USD"</td><td>"EQXR_VT10"</td><td>-0.549983</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>"USD"</td><td>"EQXR_VT10"</td><td>-1.198544</td><td>1.0</td><td>0</td><td>0</td></tr></tbody></table></div>"
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],
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"text/plain": [
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"shape: (20, 7)\n",
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"┌────────────┬─────┬───────────┬───────────┬─────────┬─────────┬─────────┐\n",
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"│ real_date ┆ cid ┆ xcat ┆ value ┆ grading ┆ eop_lag ┆ mop_lag │\n",
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"│ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n",
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"│ date ┆ str ┆ str ┆ f64 ┆ f64 ┆ i64 ┆ i64 │\n",
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"╞════════════╪═════╪═══════════╪═══════════╪═════════╪═════════╪═════════╡\n",
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"│ 2024-11-14 ┆ AUD ┆ EQXR_NSA ┆ 0.329188 ┆ 1.0 ┆ 0 ┆ 0 │\n",
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"│ 2024-11-15 ┆ AUD ┆ EQXR_NSA ┆ 0.826346 ┆ 1.0 ┆ 0 ┆ 0 │\n",
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"│ 2024-11-14 ┆ CAD ┆ EQXR_NSA ┆ 0.199402 ┆ 1.0 ┆ 0 ┆ 0 │\n",
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"│ 2024-11-15 ┆ CAD ┆ EQXR_NSA ┆ -0.696517 ┆ 1.0 ┆ 0 ┆ 0 │\n",
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"│ 2024-11-14 ┆ EUR ┆ EQXR_NSA ┆ 2.024889 ┆ 1.0 ┆ 0 ┆ 0 │\n",
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"│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n",
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"│ 2024-11-15 ┆ EUR ┆ EQXR_VT10 ┆ -0.477901 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
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"│ 2024-11-14 ┆ GBP ┆ EQXR_VT10 ┆ 0.664208 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
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"│ 2024-11-15 ┆ GBP ┆ EQXR_VT10 ┆ -0.068778 ┆ 1.0 ┆ 0 ┆ 0 │\n",
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"│ 2024-11-14 ┆ USD ┆ EQXR_VT10 ┆ -0.549983 ┆ 1.0 ┆ 0 ┆ 0 │\n",
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"│ 2024-11-15 ┆ USD ┆ EQXR_VT10 ┆ -1.198544 ┆ 1.0 ┆ 0 ┆ 0 │\n",
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"└────────────┴─────┴───────────┴───────────┴─────────┴─────────┴─────────┘"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"eq_df = msyrs.qdf.reduce_dataframe(\n",
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" df=big_df,\n",
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" cids=sel_cids,\n",
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" xcats=[\"EQXR_NSA\", \"EQXR_VT10\"],\n",
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" start=start,\n",
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")\n",
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"eq_df"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [],
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"source": [
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"fx_xcats = [xc for xc in xcats if xc.startswith(\"FX\")]\n",
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"fx_df = msyrs.qdf.reduce_dataframe(\n",
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" df=big_df, cids=sel_cids, start=start, xcats=fx_xcats, intersect=True\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
|
||||
"<div><style>\n",
|
||||
".dataframe > thead > tr,\n",
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".dataframe > tbody > tr {\n",
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||||
" text-align: right;\n",
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||||
" white-space: pre-wrap;\n",
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"}\n",
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"</style>\n",
|
||||
"<small>shape: (10, 7)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>real_date</th><th>cid</th><th>xcat</th><th>value</th><th>grading</th><th>eop_lag</th><th>mop_lag</th></tr><tr><td>date</td><td>str</td><td>str</td><td>f64</td><td>f64</td><td>i64</td><td>i64</td></tr></thead><tbody><tr><td>2024-11-14</td><td>"AUD"</td><td>"EQXR_NSA"</td><td>0.329188</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>"AUD"</td><td>"EQXR_NSA"</td><td>0.826346</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>"CAD"</td><td>"EQXR_NSA"</td><td>0.199402</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>"CAD"</td><td>"EQXR_NSA"</td><td>-0.696517</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>"EUR"</td><td>"EQXR_NSA"</td><td>2.024889</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>"EUR"</td><td>"EQXR_NSA"</td><td>-0.661567</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>"GBP"</td><td>"EQXR_NSA"</td><td>0.596533</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>"GBP"</td><td>"EQXR_NSA"</td><td>-0.06177</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>"USD"</td><td>"EQXR_NSA"</td><td>-0.627493</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>"USD"</td><td>"EQXR_NSA"</td><td>-1.367457</td><td>1.0</td><td>0</td><td>0</td></tr></tbody></table></div>"
|
||||
],
|
||||
"text/plain": [
|
||||
"shape: (10, 7)\n",
|
||||
"┌────────────┬─────┬──────────┬───────────┬─────────┬─────────┬─────────┐\n",
|
||||
"│ real_date ┆ cid ┆ xcat ┆ value ┆ grading ┆ eop_lag ┆ mop_lag │\n",
|
||||
"│ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n",
|
||||
"│ date ┆ str ┆ str ┆ f64 ┆ f64 ┆ i64 ┆ i64 │\n",
|
||||
"╞════════════╪═════╪══════════╪═══════════╪═════════╪═════════╪═════════╡\n",
|
||||
"│ 2024-11-14 ┆ AUD ┆ EQXR_NSA ┆ 0.329188 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-15 ┆ AUD ┆ EQXR_NSA ┆ 0.826346 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-14 ┆ CAD ┆ EQXR_NSA ┆ 0.199402 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-15 ┆ CAD ┆ EQXR_NSA ┆ -0.696517 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-14 ┆ EUR ┆ EQXR_NSA ┆ 2.024889 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-15 ┆ EUR ┆ EQXR_NSA ┆ -0.661567 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-14 ┆ GBP ┆ EQXR_NSA ┆ 0.596533 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-15 ┆ GBP ┆ EQXR_NSA ┆ -0.06177 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-14 ┆ USD ┆ EQXR_NSA ┆ -0.627493 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-15 ┆ USD ┆ EQXR_NSA ┆ -1.367457 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"└────────────┴─────┴──────────┴───────────┴─────────┴─────────┴─────────┘"
|
||||
]
|
||||
},
|
||||
"execution_count": 10,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"new_df: pl.DataFrame = msyrs.qdf.update_dataframe(df=eq_df, df_add=fx_df)\n",
|
||||
"\n",
|
||||
"new_df.head(10)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 11,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div><style>\n",
|
||||
".dataframe > thead > tr,\n",
|
||||
".dataframe > tbody > tr {\n",
|
||||
" text-align: right;\n",
|
||||
" white-space: pre-wrap;\n",
|
||||
"}\n",
|
||||
"</style>\n",
|
||||
"<small>shape: (10, 7)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>real_date</th><th>cid</th><th>xcat</th><th>value</th><th>grading</th><th>eop_lag</th><th>mop_lag</th></tr><tr><td>date</td><td>str</td><td>str</td><td>f64</td><td>f64</td><td>i64</td><td>i64</td></tr></thead><tbody><tr><td>2024-11-14</td><td>"GBP"</td><td>"FXXR_NSA"</td><td>-0.067809</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>"GBP"</td><td>"FXXR_NSA"</td><td>-0.430055</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>"AUD"</td><td>"FXXR_VT10"</td><td>-0.4294</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>"AUD"</td><td>"FXXR_VT10"</td><td>-0.452535</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>"CAD"</td><td>"FXXR_VT10"</td><td>-1.132314</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>"CAD"</td><td>"FXXR_VT10"</td><td>-1.755605</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>"EUR"</td><td>"FXXR_VT10"</td><td>-0.292422</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>"EUR"</td><td>"FXXR_VT10"</td><td>-0.855108</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>"GBP"</td><td>"FXXR_VT10"</td><td>-0.110526</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>"GBP"</td><td>"FXXR_VT10"</td><td>-0.700977</td><td>1.0</td><td>0</td><td>0</td></tr></tbody></table></div>"
|
||||
],
|
||||
"text/plain": [
|
||||
"shape: (10, 7)\n",
|
||||
"┌────────────┬─────┬───────────┬───────────┬─────────┬─────────┬─────────┐\n",
|
||||
"│ real_date ┆ cid ┆ xcat ┆ value ┆ grading ┆ eop_lag ┆ mop_lag │\n",
|
||||
"│ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n",
|
||||
"│ date ┆ str ┆ str ┆ f64 ┆ f64 ┆ i64 ┆ i64 │\n",
|
||||
"╞════════════╪═════╪═══════════╪═══════════╪═════════╪═════════╪═════════╡\n",
|
||||
"│ 2024-11-14 ┆ GBP ┆ FXXR_NSA ┆ -0.067809 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-15 ┆ GBP ┆ FXXR_NSA ┆ -0.430055 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-14 ┆ AUD ┆ FXXR_VT10 ┆ -0.4294 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-15 ┆ AUD ┆ FXXR_VT10 ┆ -0.452535 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-14 ┆ CAD ┆ FXXR_VT10 ┆ -1.132314 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-15 ┆ CAD ┆ FXXR_VT10 ┆ -1.755605 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-14 ┆ EUR ┆ FXXR_VT10 ┆ -0.292422 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-15 ┆ EUR ┆ FXXR_VT10 ┆ -0.855108 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-14 ┆ GBP ┆ FXXR_VT10 ┆ -0.110526 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"│ 2024-11-15 ┆ GBP ┆ FXXR_VT10 ┆ -0.700977 ┆ 1.0 ┆ 0 ┆ 0 │\n",
|
||||
"└────────────┴─────┴───────────┴───────────┴─────────┴─────────┴─────────┘"
|
||||
]
|
||||
},
|
||||
"execution_count": 11,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"new_df.tail(10)"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": ".venv",
|
||||
"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": "3.12.7"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
@@ -1,5 +1,32 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "31d0d7e3",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Running this noteboook\n",
|
||||
"\n",
|
||||
"Create a new Python Venv using:\n",
|
||||
"\n",
|
||||
"```bash\n",
|
||||
"python -m venv .venv\n",
|
||||
"# source .venv/bin/activate\n",
|
||||
"./.venv/Scripts/activate\n",
|
||||
"```\n",
|
||||
"\n",
|
||||
"Install `evcxr_jupyter` and `jupyterlab` using:\n",
|
||||
"\n",
|
||||
"```bash\n",
|
||||
"cargo install evcxr_jupyter\n",
|
||||
"evcxr_jupyter --install\n",
|
||||
"pip install jupyterlab\n",
|
||||
"jupyter lab\n",
|
||||
"```\n",
|
||||
"\n",
|
||||
"Or try following this guide here: [DataCrayon - Setup Jupyter with Rust](https://datacrayon.com/data-analysis-with-rust-notebooks/setup-anaconda-jupyter-and-rust/)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "8d04a212-4025-41d7-809e-864649b08ab5",
|
||||
@@ -21,7 +48,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"execution_count": null,
|
||||
"id": "22e1ae9e-14b8-4be4-b852-8f0fb420eaca",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
@@ -399,7 +426,7 @@
|
||||
"mimetype": "text/rust",
|
||||
"name": "rust",
|
||||
"pygment_lexer": "rust",
|
||||
"version": ""
|
||||
"version": "3.12.7"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
44
notebooks/test.py
Normal file
44
notebooks/test.py
Normal file
@@ -0,0 +1,44 @@
|
||||
import msyrs
|
||||
import datetime
|
||||
|
||||
# "E:\Work\jpmaqs-data\data\ADPEMPL_SA_P1M1ML1\USD_ADPEMPL_SA_P1M1ML1.csv"
|
||||
|
||||
DATA_FOLDER_PATH = "E:/Work/jpmaqs-data"
|
||||
|
||||
dfpath = f"{DATA_FOLDER_PATH}/data/ADPEMPL_SA_P1M1ML1/USD_ADPEMPL_SA_P1M1ML1.csv"
|
||||
|
||||
print(msyrs.qdf.load_qdf(dfpath))
|
||||
|
||||
cids_dm = "AUD.CAD.CHF.EUR.GBP.JPY.NOK.NZD.SEK.USD".split(".")
|
||||
cids_em = "CLP.COP.CZK.HUF.IDR.ILS.INR.KRW.MXN.PLN.THB.TRY.TWD.ZAR".split(".")
|
||||
cids = cids_dm + cids_em
|
||||
cids_dux = list(set(cids) - set(["IDR", "NZD"]))
|
||||
ecos = "CPIC_SA_P1M1ML12.CPIC_SJA_P3M3ML3AR.CPIC_SJA_P6M6ML6AR.CPIH_SA_P1M1ML12.CPIH_SJA_P3M3ML3AR.CPIH_SJA_P6M6ML6AR.INFTEFF_NSA.INTRGDP_NSA_P1M1ML12_3MMA.INTRGDPv5Y_NSA_P1M1ML12_3MMA.PCREDITGDP_SJA_D1M1ML12.RGDP_SA_P1Q1QL4_20QMA.RYLDIRS02Y_NSA.RYLDIRS05Y_NSA.PCREDITBN_SJA_P1M1ML12".split(
|
||||
"."
|
||||
)
|
||||
mkts = "DU02YXR_NSA.DU05YXR_NSA.DU02YXR_VT10.DU05YXR_VT10.EQXR_NSA.EQXR_VT10.FXXR_NSA.FXXR_VT10.FXCRR_NSA.FXTARGETED_NSA.FXUNTRADABLE_NSA".split(
|
||||
"."
|
||||
)
|
||||
xcats = ecos + mkts
|
||||
|
||||
tickers = [f"{c}_{x}" for c in cids for x in xcats]
|
||||
|
||||
|
||||
# load_qdf_from_download_bank
|
||||
|
||||
df = msyrs.qdf.load_qdf_from_download_bank(
|
||||
folder_path=DATA_FOLDER_PATH, tickers=tickers
|
||||
)
|
||||
print(df)
|
||||
|
||||
start_date = (datetime.datetime.now() - datetime.timedelta(days=5)).strftime("%Y-%m-%d")
|
||||
|
||||
sel_cids = ["AUD", "USD", "GBP", "CAD", "JPY", "EUR"]
|
||||
df_eq = msyrs.qdf.reduce_dataframe(
|
||||
df=df, cids=["AUD"], xcats=["EQXR_NSA"], start=start_date
|
||||
)
|
||||
print(df_eq)
|
||||
|
||||
fx_xcats = [xc for xc in xcats if xc.startswith("FX")]
|
||||
df_fx = msyrs.qdf.reduce_dataframe(df=df, xcats=fx_xcats, intersect=True)
|
||||
print(df_fx)
|
||||
Reference in New Issue
Block a user