168 lines
9.9 KiB
Plaintext
168 lines
9.9 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "dd67dcdf",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pygwalker as pyg\n",
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"import polars as pl\n",
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"df = pl.read_csv('./298040/day/candle-day-250.csv',try_parse_dates = True)\n",
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"gwalker = pyg.walk(df)\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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"id": "f22b1844",
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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 > th,\n",
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".dataframe > tbody > tr > td {\n",
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" text-align: right;\n",
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"}\n",
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"</style>\n",
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"<small>shape: (14, 13)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>stockBusinessDate</th><th>stockClosingPrice</th><th>stockOpenningPrice</th><th>highestStockPrice</th><th>lowestStockPrice</th><th>accumulatedVolume</th><th>accumulatedTradingAmount</th><th>exDivision</th><th>partitionRate</th><th>partitionModifiable</th><th>previousDayVariableRatioSign</th><th>previousDayVariableRatio</th><th>revaluationIssueReason</th></tr><tr><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>f64</td><td>str</td><td>i64</td><td>i64</td><td>str</td></tr></thead><tbody><tr><td>20230615</td><td>91200</td><td>91200</td><td>91200</td><td>91200</td><td>0</td><td>0</td><td>0</td><td>0.0</td><td>"Y"</td><td>0</td><td>0</td><td>null</td></tr><tr><td>20230614</td><td>91200</td><td>93000</td><td>93500</td><td>89700</td><td>91400</td><td>8355483800</td><td>0</td><td>0.0</td><td>"Y"</td><td>5</td><td>-1800</td><td>null</td></tr><tr><td>20230613</td><td>93000</td><td>94400</td><td>96100</td><td>92500</td><td>58177</td><td>5474920900</td><td>0</td><td>0.0</td><td>"Y"</td><td>5</td><td>-1400</td><td>null</td></tr><tr><td>20230612</td><td>94400</td><td>95100</td><td>96000</td><td>92500</td><td>90459</td><td>8527275800</td><td>0</td><td>0.0</td><td>"Y"</td><td>5</td><td>-1100</td><td>null</td></tr><tr><td>20230609</td><td>95500</td><td>91600</td><td>95500</td><td>91600</td><td>153317</td><td>14460674700</td><td>0</td><td>0.0</td><td>"Y"</td><td>2</td><td>4800</td><td>null</td></tr><tr><td>20230608</td><td>90700</td><td>90400</td><td>93200</td><td>89900</td><td>111594</td><td>10221020300</td><td>0</td><td>0.0</td><td>"Y"</td><td>2</td><td>700</td><td>null</td></tr><tr><td>20230607</td><td>90000</td><td>87700</td><td>91700</td><td>86600</td><td>130728</td><td>11727784400</td><td>0</td><td>0.0</td><td>"Y"</td><td>2</td><td>2000</td><td>null</td></tr><tr><td>20230605</td><td>88000</td><td>88200</td><td>88900</td><td>87000</td><td>76802</td><td>6752970000</td><td>0</td><td>0.0</td><td>"Y"</td><td>5</td><td>-300</td><td>null</td></tr><tr><td>20230602</td><td>88300</td><td>83200</td><td>88500</td><td>82700</td><td>197737</td><td>17174200500</td><td>0</td><td>0.0</td><td>"Y"</td><td>2</td><td>6600</td><td>null</td></tr><tr><td>20230601</td><td>81700</td><td>79600</td><td>82400</td><td>79500</td><td>58524</td><td>4764621000</td><td>0</td><td>0.0</td><td>"Y"</td><td>2</td><td>1700</td><td>null</td></tr><tr><td>20230531</td><td>80000</td><td>80100</td><td>82300</td><td>79900</td><td>72863</td><td>5918119600</td><td>0</td><td>0.0</td><td>"Y"</td><td>5</td><td>-600</td><td>null</td></tr><tr><td>20230530</td><td>80600</td><td>78700</td><td>81000</td><td>78700</td><td>42843</td><td>3430568900</td><td>0</td><td>0.0</td><td>"Y"</td><td>2</td><td>1300</td><td>null</td></tr><tr><td>20230526</td><td>79300</td><td>81400</td><td>82100</td><td>79100</td><td>63816</td><td>5100281800</td><td>0</td><td>0.0</td><td>"Y"</td><td>5</td><td>-2200</td><td>null</td></tr><tr><td>20230525</td><td>81500</td><td>84000</td><td>84800</td><td>81400</td><td>68134</td><td>5642073400</td><td>0</td><td>0.0</td><td>"Y"</td><td>5</td><td>-2900</td><td>null</td></tr></tbody></table></div>"
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],
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"text/plain": [
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"shape: (14, 13)\n",
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"┌────────────┬────────────┬────────────┬────────────┬───┬────────────┬────────────┬────────────┬────────────┐\n",
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"│ stockBusin ┆ stockClosi ┆ stockOpenn ┆ highestSto ┆ … ┆ partitionM ┆ previousDa ┆ previousDa ┆ revaluatio │\n",
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"│ essDate ┆ ngPrice ┆ ingPrice ┆ ckPrice ┆ ┆ odifiable ┆ yVariableR ┆ yVariableR ┆ nIssueReas │\n",
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"│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ atioSign ┆ atio ┆ on │\n",
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"│ i64 ┆ i64 ┆ i64 ┆ i64 ┆ ┆ str ┆ --- ┆ --- ┆ --- │\n",
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"│ ┆ ┆ ┆ ┆ ┆ ┆ i64 ┆ i64 ┆ str │\n",
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"╞════════════╪════════════╪════════════╪════════════╪═══╪════════════╪════════════╪════════════╪════════════╡\n",
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"│ 20230615 ┆ 91200 ┆ 91200 ┆ 91200 ┆ … ┆ Y ┆ 0 ┆ 0 ┆ null │\n",
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"│ 20230614 ┆ 91200 ┆ 93000 ┆ 93500 ┆ … ┆ Y ┆ 5 ┆ -1800 ┆ null │\n",
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"│ 20230613 ┆ 93000 ┆ 94400 ┆ 96100 ┆ … ┆ Y ┆ 5 ┆ -1400 ┆ null │\n",
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"│ 20230612 ┆ 94400 ┆ 95100 ┆ 96000 ┆ … ┆ Y ┆ 5 ┆ -1100 ┆ null │\n",
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"│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n",
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"│ 20230531 ┆ 80000 ┆ 80100 ┆ 82300 ┆ … ┆ Y ┆ 5 ┆ -600 ┆ null │\n",
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"│ 20230530 ┆ 80600 ┆ 78700 ┆ 81000 ┆ … ┆ Y ┆ 2 ┆ 1300 ┆ null │\n",
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"│ 20230526 ┆ 79300 ┆ 81400 ┆ 82100 ┆ … ┆ Y ┆ 5 ┆ -2200 ┆ null │\n",
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"│ 20230525 ┆ 81500 ┆ 84000 ┆ 84800 ┆ … ┆ Y ┆ 5 ┆ -2900 ┆ null │\n",
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"└────────────┴────────────┴────────────┴────────────┴───┴────────────┴────────────┴────────────┴────────────┘"
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]
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},
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"execution_count": 2,
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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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"df.sort(\"stockBusinessDate\", descending=True).limit(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": 42,
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"id": "175e5213",
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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 > th,\n",
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".dataframe > tbody > tr > td {\n",
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" text-align: right;\n",
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"}\n",
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"</style>\n",
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"<small>shape: (1, 2)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>up</th><th>down</th></tr><tr><td>i64</td><td>i64</td></tr></thead><tbody><tr><td>17100</td><td>-10300</td></tr></tbody></table></div>"
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],
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"text/plain": [
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"shape: (1, 2)\n",
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"┌───────┬────────┐\n",
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"│ up ┆ down │\n",
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"│ --- ┆ --- │\n",
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"│ i64 ┆ i64 │\n",
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"╞═══════╪════════╡\n",
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"│ 17100 ┆ -10300 │\n",
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"└───────┴────────┘"
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]
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},
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"execution_count": 42,
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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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"\n",
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"def up(val: int) -> int:\n",
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" if val > 0 :\n",
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" return val\n",
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" else:\n",
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" return 0\n",
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"\n",
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"def down(val: int) -> int:\n",
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" if val < 0 :\n",
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" return val\n",
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" else: return 0\n",
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"\n",
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"#df.sort(\"stockBusinessDate\", descending=True).select([pl.col(\"previousDayVariableRatio\").apply(up).sum().alias(\"up\"), pl.col(\"previousDayVariableRatio\").apply(down).sum().alias(\"down\")]).limit(14)\n",
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"df.sort(\"stockBusinessDate\", descending=True).limit(14).select([pl.col(\"previousDayVariableRatio\").apply(up).sum().alias(\"up\"), pl.col(\"previousDayVariableRatio\").apply(down).sum().alias(\"down\")])"
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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": null,
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"id": "01cfce5c",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "bfaec855",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "dde44c3d",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "10cf7163",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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