优化金字塔选股结果格式
This commit is contained in:
1
.gitignore
vendored
1
.gitignore
vendored
@@ -117,3 +117,4 @@ cython_debug/
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# Custom
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temp/
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temp/**/*
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.idea/**/csv-editor.xml
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196
材料准备/财报信息.ipynb
196
材料准备/财报信息.ipynb
@@ -4,7 +4,11 @@
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"cell_type": "code",
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"id": "initial_id",
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"metadata": {
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"collapsed": true
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"collapsed": true,
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"ExecuteTime": {
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"end_time": "2025-01-13T01:30:08.643756Z",
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"start_time": "2025-01-13T01:30:06.177472Z"
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}
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},
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"source": [
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"import pandas as pd\n",
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@@ -13,10 +17,15 @@
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"ts_pro = ts.pro_api(token=\"64ebff4fa679167600b905ee45dd88e76f3963c0ff39157f3f085f0e\")"
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],
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"outputs": [],
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"execution_count": null
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"execution_count": 1
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},
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{
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"metadata": {},
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-01-13T01:30:08.652416Z",
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"start_time": "2025-01-13T01:30:08.646084Z"
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}
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},
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"cell_type": "code",
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"source": [
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"def get_balance_sheet_df(start_year, end_year):\n",
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@@ -59,10 +68,15 @@
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],
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"id": "14a28ff4952f0df8",
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"outputs": [],
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"execution_count": null
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"execution_count": 2
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},
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{
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"metadata": {},
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-01-13T01:30:08.656800Z",
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"start_time": "2025-01-13T01:30:08.653794Z"
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}
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},
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"cell_type": "code",
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"source": [
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"start_year = 2014\n",
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@@ -70,10 +84,15 @@
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],
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"id": "dc68cde196159626",
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"outputs": [],
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"execution_count": null
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"execution_count": 3
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},
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{
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"metadata": {},
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-01-13T01:39:39.349170Z",
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"start_time": "2025-01-13T01:30:08.660347Z"
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}
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},
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"cell_type": "code",
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"source": [
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"# 财务负债表\n",
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@@ -81,33 +100,168 @@
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"balance_sheet_df.to_csv(\"../temp/balance_sheet.csv\", index=False)"
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],
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"id": "33cd797a12ad567e",
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"outputs": [],
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"execution_count": null
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Pull balance sheet: 2014\n",
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"Pull balance sheet: 2015\n"
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]
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},
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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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"/var/folders/7h/w0cmp4zj6mn9br_6nyj310m40000gn/T/ipykernel_50121/709533518.py:8: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
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" result = pd.concat([result, temp], ignore_index=True)\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Pull balance sheet: 2016\n",
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"Pull balance sheet: 2017\n",
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"Pull balance sheet: 2018\n",
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"Pull balance sheet: 2019\n",
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"Pull balance sheet: 2020\n",
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"Pull balance sheet: 2021\n",
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"Pull balance sheet: 2022\n",
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"Pull balance sheet: 2023\n",
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"Pull balance sheet: 2024\n"
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]
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},
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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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"/var/folders/7h/w0cmp4zj6mn9br_6nyj310m40000gn/T/ipykernel_50121/709533518.py:8: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
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" result = pd.concat([result, temp], ignore_index=True)\n"
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]
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}
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],
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"execution_count": 4
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},
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{
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"metadata": {},
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-01-13T01:43:28.007135Z",
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"start_time": "2025-01-13T01:39:39.363037Z"
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}
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},
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"cell_type": "code",
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"source": [
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"income_df = clean_df(get_income_df(start_year, end_year))\n",
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"income_df.to_csv(\"../temp/income.csv\", index=False)"
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],
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"id": "17306c1524f5e173",
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"outputs": [],
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"execution_count": null
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Pull income: 2014\n",
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"Pull income: 2015\n"
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]
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},
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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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"/var/folders/7h/w0cmp4zj6mn9br_6nyj310m40000gn/T/ipykernel_50121/709533518.py:19: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
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" result = pd.concat([result, temp], ignore_index=True)\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Pull income: 2016\n",
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"Pull income: 2017\n",
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"Pull income: 2018\n",
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"Pull income: 2019\n",
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"Pull income: 2020\n",
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"Pull income: 2021\n",
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"Pull income: 2022\n",
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"Pull income: 2023\n",
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"Pull income: 2024\n"
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]
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},
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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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"/var/folders/7h/w0cmp4zj6mn9br_6nyj310m40000gn/T/ipykernel_50121/709533518.py:19: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
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" result = pd.concat([result, temp], ignore_index=True)\n"
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]
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}
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],
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"execution_count": 5
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},
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{
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"metadata": {},
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-01-13T01:46:46.375157Z",
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"start_time": "2025-01-13T01:43:28.011213Z"
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}
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},
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"cell_type": "code",
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"source": [
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"cash_flow_df = clean_df(get_cash_flow_df(start_year, end_year))\n",
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"cash_flow_df.to_csv(\"../temp/cash_flow.csv\", index=False)"
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],
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"id": "334dbe20f2047a1e",
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"outputs": [],
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"execution_count": null
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Pull cash flow: 2014\n",
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"Pull cash flow: 2015\n"
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]
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},
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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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"/var/folders/7h/w0cmp4zj6mn9br_6nyj310m40000gn/T/ipykernel_50121/709533518.py:30: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
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" result = pd.concat([result, temp], ignore_index=True)\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Pull cash flow: 2016\n",
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"Pull cash flow: 2017\n",
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"Pull cash flow: 2018\n",
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"Pull cash flow: 2019\n",
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"Pull cash flow: 2020\n",
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"Pull cash flow: 2021\n",
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"Pull cash flow: 2022\n",
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"Pull cash flow: 2023\n",
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"Pull cash flow: 2024\n"
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]
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},
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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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"/var/folders/7h/w0cmp4zj6mn9br_6nyj310m40000gn/T/ipykernel_50121/709533518.py:30: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
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" result = pd.concat([result, temp], ignore_index=True)\n"
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]
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}
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],
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"execution_count": 6
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},
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{
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"metadata": {},
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-01-13T01:46:57.717599Z",
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"start_time": "2025-01-13T01:46:46.377806Z"
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}
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},
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"cell_type": "code",
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"source": [
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"finance_df = pd.merge(balance_sheet_df, income_df, on=[\"ts_code\", \"end_date\"])\n",
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@@ -116,13 +270,13 @@
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],
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"id": "f8bea62f377b5e2",
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"outputs": [],
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"execution_count": null
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"execution_count": 7
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-01-12T12:04:00.424439Z",
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"start_time": "2025-01-12T12:04:00.364557Z"
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"end_time": "2025-01-13T01:46:57.814028Z",
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"start_time": "2025-01-13T01:46:57.728111Z"
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}
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},
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"cell_type": "code",
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@@ -512,12 +666,12 @@
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"</div>"
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]
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},
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"execution_count": 29,
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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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"execution_count": 29
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"execution_count": 8
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}
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],
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"metadata": {
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40816
财报筛选/金字塔选股.ipynb
40816
财报筛选/金字塔选股.ipynb
File diff suppressed because it is too large
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