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Palash Tyagi 2024-11-19 01:15:52 +00:00
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commit 1ea698a1e2
5 changed files with 75 additions and 268 deletions
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@ -42,7 +42,7 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@ -62,7 +62,7 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@ -71,53 +71,21 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# DATA_FOLDER_PATH = \"E:/Work/jpmaqs-data\"\n",
"DATA_FOLDER_PATH = \"C:/Users/PalashTyagi/Code/go-dataquery/jpmaqs-data\"\n",
"DATA_FOLDER_PATH = \"E:/Work/jpmaqs-data\"\n",
"# DATA_FOLDER_PATH = \"C:/Users/PalashTyagi/Code/go-dataquery/jpmaqs-data\"\n",
"DQ_CLIENT_ID = os.getenv(\"DQ_CLIENT_ID\")\n",
"DQ_CLIENT_SECRET = os.getenv(\"DQ_CLIENT_SECRET\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": null,
"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: (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>&quot;USD&quot;</td><td>&quot;ADPEMPL_SA_P1M1ML1&quot;</td><td>-0.173806</td><td>3.0</td><td>3</td><td>33</td></tr><tr><td>2010-03-04</td><td>&quot;USD&quot;</td><td>&quot;ADPEMPL_SA_P1M1ML1&quot;</td><td>-0.173806</td><td>3.0</td><td>4</td><td>34</td></tr><tr><td>2010-03-05</td><td>&quot;USD&quot;</td><td>&quot;ADPEMPL_SA_P1M1ML1&quot;</td><td>-0.173806</td><td>3.0</td><td>5</td><td>35</td></tr><tr><td>2010-03-08</td><td>&quot;USD&quot;</td><td>&quot;ADPEMPL_SA_P1M1ML1&quot;</td><td>-0.173806</td><td>3.0</td><td>8</td><td>38</td></tr><tr><td>2010-03-09</td><td>&quot;USD&quot;</td><td>&quot;ADPEMPL_SA_P1M1ML1&quot;</td><td>-0.173806</td><td>3.0</td><td>9</td><td>39</td></tr></tbody></table></div>"
],
"text/plain": [
"shape: (5, 7)\n",
"┌────────────┬─────┬────────────────────┬───────────┬─────────┬─────────┬─────────┐\n",
"│ real_date ┆ cid ┆ xcat ┆ value ┆ grading ┆ eop_lag ┆ mop_lag │\n",
"│ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n",
"│ date ┆ str ┆ str ┆ f64 ┆ f64 ┆ i64 ┆ i64 │\n",
"╞════════════╪═════╪════════════════════╪═══════════╪═════════╪═════════╪═════════╡\n",
"│ 2010-03-03 ┆ USD ┆ ADPEMPL_SA_P1M1ML1 ┆ -0.173806 ┆ 3.0 ┆ 3 ┆ 33 │\n",
"│ 2010-03-04 ┆ USD ┆ ADPEMPL_SA_P1M1ML1 ┆ -0.173806 ┆ 3.0 ┆ 4 ┆ 34 │\n",
"│ 2010-03-05 ┆ USD ┆ ADPEMPL_SA_P1M1ML1 ┆ -0.173806 ┆ 3.0 ┆ 5 ┆ 35 │\n",
"│ 2010-03-08 ┆ USD ┆ ADPEMPL_SA_P1M1ML1 ┆ -0.173806 ┆ 3.0 ┆ 8 ┆ 38 │\n",
"│ 2010-03-09 ┆ USD ┆ ADPEMPL_SA_P1M1ML1 ┆ -0.173806 ┆ 3.0 ┆ 9 ┆ 39 │\n",
"└────────────┴─────┴────────────────────┴───────────┴─────────┴─────────┴─────────┘"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"dfpath = f\"{DATA_FOLDER_PATH}/data/ADPEMPL_SA_P1M1ML1/USD_ADPEMPL_SA_P1M1ML1.csv\"\n",
"\n",
@ -128,7 +96,7 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@ -151,41 +119,9 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": null,
"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: (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>f64</td><td>f64</td></tr></thead><tbody><tr><td>1990-04-26</td><td>&quot;AUD&quot;</td><td>&quot;CPIC_SA_P1M1ML12&quot;</td><td>6.434599</td><td>2.0</td><td>26.0</td><td>223.0</td></tr><tr><td>1990-04-27</td><td>&quot;AUD&quot;</td><td>&quot;CPIC_SA_P1M1ML12&quot;</td><td>6.434599</td><td>2.0</td><td>27.0</td><td>224.0</td></tr><tr><td>1990-04-30</td><td>&quot;AUD&quot;</td><td>&quot;CPIC_SA_P1M1ML12&quot;</td><td>6.434599</td><td>2.0</td><td>30.0</td><td>227.0</td></tr><tr><td>1990-05-01</td><td>&quot;AUD&quot;</td><td>&quot;CPIC_SA_P1M1ML12&quot;</td><td>6.434599</td><td>2.0</td><td>31.0</td><td>228.0</td></tr><tr><td>1990-05-02</td><td>&quot;AUD&quot;</td><td>&quot;CPIC_SA_P1M1ML12&quot;</td><td>6.434599</td><td>2.0</td><td>32.0</td><td>229.0</td></tr></tbody></table></div>"
],
"text/plain": [
"shape: (5, 7)\n",
"┌────────────┬─────┬──────────────────┬──────────┬─────────┬─────────┬─────────┐\n",
"│ real_date ┆ cid ┆ xcat ┆ value ┆ grading ┆ eop_lag ┆ mop_lag │\n",
"│ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n",
"│ date ┆ str ┆ str ┆ f64 ┆ f64 ┆ f64 ┆ f64 │\n",
"╞════════════╪═════╪══════════════════╪══════════╪═════════╪═════════╪═════════╡\n",
"│ 1990-04-26 ┆ AUD ┆ CPIC_SA_P1M1ML12 ┆ 6.434599 ┆ 2.0 ┆ 26.0 ┆ 223.0 │\n",
"│ 1990-04-27 ┆ AUD ┆ CPIC_SA_P1M1ML12 ┆ 6.434599 ┆ 2.0 ┆ 27.0 ┆ 224.0 │\n",
"│ 1990-04-30 ┆ AUD ┆ CPIC_SA_P1M1ML12 ┆ 6.434599 ┆ 2.0 ┆ 30.0 ┆ 227.0 │\n",
"│ 1990-05-01 ┆ AUD ┆ CPIC_SA_P1M1ML12 ┆ 6.434599 ┆ 2.0 ┆ 31.0 ┆ 228.0 │\n",
"│ 1990-05-02 ┆ AUD ┆ CPIC_SA_P1M1ML12 ┆ 6.434599 ┆ 2.0 ┆ 32.0 ┆ 229.0 │\n",
"└────────────┴─────┴──────────────────┴──────────┴─────────┴─────────┴─────────┘"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"downloaded_df: pl.DataFrame = msyrs.download.download_jpmaqs_indicators_as_df(\n",
" client_id=DQ_CLIENT_ID,\n",
@ -197,41 +133,9 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": null,
"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: (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>&quot;AUD&quot;</td><td>&quot;CPIC_SA_P1M1ML12&quot;</td><td>6.434599</td><td>2.0</td><td>26</td><td>223</td></tr><tr><td>1990-04-27</td><td>&quot;AUD&quot;</td><td>&quot;CPIC_SA_P1M1ML12&quot;</td><td>6.434599</td><td>2.0</td><td>27</td><td>224</td></tr><tr><td>1990-04-30</td><td>&quot;AUD&quot;</td><td>&quot;CPIC_SA_P1M1ML12&quot;</td><td>6.434599</td><td>2.0</td><td>30</td><td>227</td></tr><tr><td>1990-05-01</td><td>&quot;AUD&quot;</td><td>&quot;CPIC_SA_P1M1ML12&quot;</td><td>6.434599</td><td>2.0</td><td>31</td><td>228</td></tr><tr><td>1990-05-02</td><td>&quot;AUD&quot;</td><td>&quot;CPIC_SA_P1M1ML12&quot;</td><td>6.434599</td><td>2.0</td><td>32</td><td>229</td></tr></tbody></table></div>"
],
"text/plain": [
"shape: (5, 7)\n",
"┌────────────┬─────┬──────────────────┬──────────┬─────────┬─────────┬─────────┐\n",
"│ real_date ┆ cid ┆ xcat ┆ value ┆ grading ┆ eop_lag ┆ mop_lag │\n",
"│ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n",
"│ date ┆ str ┆ str ┆ f64 ┆ f64 ┆ i64 ┆ i64 │\n",
"╞════════════╪═════╪══════════════════╪══════════╪═════════╪═════════╪═════════╡\n",
"│ 1990-04-26 ┆ AUD ┆ CPIC_SA_P1M1ML12 ┆ 6.434599 ┆ 2.0 ┆ 26 ┆ 223 │\n",
"│ 1990-04-27 ┆ AUD ┆ CPIC_SA_P1M1ML12 ┆ 6.434599 ┆ 2.0 ┆ 27 ┆ 224 │\n",
"│ 1990-04-30 ┆ AUD ┆ CPIC_SA_P1M1ML12 ┆ 6.434599 ┆ 2.0 ┆ 30 ┆ 227 │\n",
"│ 1990-05-01 ┆ AUD ┆ CPIC_SA_P1M1ML12 ┆ 6.434599 ┆ 2.0 ┆ 31 ┆ 228 │\n",
"│ 1990-05-02 ┆ AUD ┆ CPIC_SA_P1M1ML12 ┆ 6.434599 ┆ 2.0 ┆ 32 ┆ 229 │\n",
"└────────────┴─────┴──────────────────┴──────────┴─────────┴─────────┴─────────┘"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"big_df: pl.DataFrame = msyrs.qdf.load_qdf_from_download_bank(\n",
" folder_path=DATA_FOLDER_PATH, tickers=tickers\n",
@ -243,18 +147,7 @@
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"241.2352533340454"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"big_df.estimated_size(\"mb\")"
]
@ -263,18 +156,7 @@
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"625.9191436767578"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"big_df.to_pandas().memory_usage(deep=True).sum() / 1024**2"
]
@ -283,18 +165,7 @@
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"152.3249340057373"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"macrosynergy.management.types.QuantamentalDataFrame(big_df.to_pandas()).memory_usage(\n",
" deep=True\n",
@ -303,7 +174,7 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@ -313,47 +184,9 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": null,
"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: (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>&quot;AUD&quot;</td><td>&quot;EQXR_NSA&quot;</td><td>0.329188</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>&quot;AUD&quot;</td><td>&quot;EQXR_NSA&quot;</td><td>0.826346</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>&quot;CAD&quot;</td><td>&quot;EQXR_NSA&quot;</td><td>0.199402</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>&quot;CAD&quot;</td><td>&quot;EQXR_NSA&quot;</td><td>-0.696517</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>&quot;EUR&quot;</td><td>&quot;EQXR_NSA&quot;</td><td>2.024889</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td></tr><tr><td>2024-11-15</td><td>&quot;EUR&quot;</td><td>&quot;EQXR_VT10&quot;</td><td>-0.477901</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>&quot;GBP&quot;</td><td>&quot;EQXR_VT10&quot;</td><td>0.664208</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>&quot;GBP&quot;</td><td>&quot;EQXR_VT10&quot;</td><td>-0.068778</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>&quot;USD&quot;</td><td>&quot;EQXR_VT10&quot;</td><td>-0.549983</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>&quot;USD&quot;</td><td>&quot;EQXR_VT10&quot;</td><td>-1.198544</td><td>1.0</td><td>0</td><td>0</td></tr></tbody></table></div>"
],
"text/plain": [
"shape: (20, 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",
"│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n",
"│ 2024-11-15 ┆ EUR ┆ EQXR_VT10 ┆ -0.477901 ┆ 1.0 ┆ 0 ┆ 0 │\n",
"│ 2024-11-14 ┆ GBP ┆ EQXR_VT10 ┆ 0.664208 ┆ 1.0 ┆ 0 ┆ 0 │\n",
"│ 2024-11-15 ┆ GBP ┆ EQXR_VT10 ┆ -0.068778 ┆ 1.0 ┆ 0 ┆ 0 │\n",
"│ 2024-11-14 ┆ USD ┆ EQXR_VT10 ┆ -0.549983 ┆ 1.0 ┆ 0 ┆ 0 │\n",
"│ 2024-11-15 ┆ USD ┆ EQXR_VT10 ┆ -1.198544 ┆ 1.0 ┆ 0 ┆ 0 │\n",
"└────────────┴─────┴───────────┴───────────┴─────────┴─────────┴─────────┘"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"eq_df = msyrs.qdf.reduce_dataframe(\n",
" df=big_df,\n",
@ -366,7 +199,7 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@ -378,46 +211,9 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": null,
"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>&quot;AUD&quot;</td><td>&quot;EQXR_NSA&quot;</td><td>0.329188</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>&quot;AUD&quot;</td><td>&quot;EQXR_NSA&quot;</td><td>0.826346</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>&quot;CAD&quot;</td><td>&quot;EQXR_NSA&quot;</td><td>0.199402</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>&quot;CAD&quot;</td><td>&quot;EQXR_NSA&quot;</td><td>-0.696517</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>&quot;EUR&quot;</td><td>&quot;EQXR_NSA&quot;</td><td>2.024889</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>&quot;EUR&quot;</td><td>&quot;EQXR_NSA&quot;</td><td>-0.661567</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>&quot;GBP&quot;</td><td>&quot;EQXR_NSA&quot;</td><td>0.596533</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>&quot;GBP&quot;</td><td>&quot;EQXR_NSA&quot;</td><td>-0.06177</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>&quot;USD&quot;</td><td>&quot;EQXR_NSA&quot;</td><td>-0.627493</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>&quot;USD&quot;</td><td>&quot;EQXR_NSA&quot;</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": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"new_df: pl.DataFrame = msyrs.qdf.update_dataframe(df=eq_df, df_add=fx_df)\n",
"\n",
@ -426,46 +222,9 @@
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": null,
"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>&quot;GBP&quot;</td><td>&quot;FXXR_NSA&quot;</td><td>-0.067809</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>&quot;GBP&quot;</td><td>&quot;FXXR_NSA&quot;</td><td>-0.430055</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>&quot;AUD&quot;</td><td>&quot;FXXR_VT10&quot;</td><td>-0.4294</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>&quot;AUD&quot;</td><td>&quot;FXXR_VT10&quot;</td><td>-0.452535</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>&quot;CAD&quot;</td><td>&quot;FXXR_VT10&quot;</td><td>-1.132314</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>&quot;CAD&quot;</td><td>&quot;FXXR_VT10&quot;</td><td>-1.755605</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>&quot;EUR&quot;</td><td>&quot;FXXR_VT10&quot;</td><td>-0.292422</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>&quot;EUR&quot;</td><td>&quot;FXXR_VT10&quot;</td><td>-0.855108</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-14</td><td>&quot;GBP&quot;</td><td>&quot;FXXR_VT10&quot;</td><td>-0.110526</td><td>1.0</td><td>0</td><td>0</td></tr><tr><td>2024-11-15</td><td>&quot;GBP&quot;</td><td>&quot;FXXR_VT10&quot;</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": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"new_df.tail(10)"
]
@ -487,7 +246,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.0"
"version": "3.12.7"
}
},
"nbformat": 4,

8
src/py/download.pyi Normal file
View File

@ -0,0 +1,8 @@
from polars import DataFrame
__all__ = [
"download_jpmaqs_indicators_as_df",
]
def download_jpmaqs_indicators_as_df(*args, **kwargs) -> DataFrame:
...

8
src/py/msyrs.pyi Normal file
View File

@ -0,0 +1,8 @@
import .download # type: ignore
import .qdf # type: ignore
__all__ = [
"download",
"qdf",
]

24
src/py/qdf.pyi Normal file
View File

@ -0,0 +1,24 @@
from polars import DataFrame
__all__ = [
"load_qdf",
"load_qdf_from_download_bank",
"reduce_dataframe",
"update_dataframe",
]
# qdf/load_qdf.pyi
def load_qdf(*args, **kwargs) -> DataFrame:
...
# qdf/load_qdf_from_download_bank.pyi
def load_qdf_from_download_bank(*args, **kwargs) -> DataFrame:
...
# qdf/reduce_dataframe.pyi
def reduce_dataframe(*args, **kwargs) -> DataFrame:
...
# qdf/update_dataframe.pyi
def update_dataframe(*args, **kwargs) -> DataFrame:
...

14
src/utils/qdf/pivots.rs
View File

@ -4,10 +4,14 @@ use polars::prelude::*;
use std::collections::HashMap;
use std::error::Error;
#[allow(unused_imports)]
use std::f32::consts::E;
/// The required columns for a Quantamental DataFrame.
const QDF_INDEX_COLUMNS: [&str; 3] = ["real_date", "cid", "xcat"];
/// Pivots a dataframe to a format where each ticker a column.
#[allow(dead_code)]
pub fn pivot_dataframe_by_ticker(
df: DataFrame,
metric: Option<String>,
@ -24,7 +28,7 @@ pub fn pivot_dataframe_by_ticker(
metric = df.get_column_names()[3].to_string();
}
let mut new_df = df.clone();
// let mut new_df = df.clone();
// keep only the index columns and the metric column
let mut keep_cols = QDF_INDEX_COLUMNS
.to_vec()
@ -33,7 +37,9 @@ pub fn pivot_dataframe_by_ticker(
.collect::<Vec<String>>();
keep_cols.push(metric.clone());
new_df = new_df.select(keep_cols)?;
return Err("Not implemented".into());
// new_df = new_df.select(keep_cols)?;
// let ticker_col = get_ticker_column_for_quantamental_dataframe(&new_df)?;
// new_df.with_column(ticker_col)?;
@ -42,9 +48,11 @@ pub fn pivot_dataframe_by_ticker(
// let dates_col = df.column("real_date")?;
Ok(df)
// Ok(df)
}
/// Splits a dataframe by ticker.
#[allow(dead_code)]
fn split_df_by_tickers(df: &DataFrame) -> Result<HashMap<String, DataFrame>, Box<dyn Error>> {
check_quantamental_dataframe(df)?;