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HaoYizhi
2023-07-03 12:40:10 +08:00
parent 9dce034cf2
commit 9ebdb89332
9 changed files with 221 additions and 31 deletions
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160
test.ipynb
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@@ -357,6 +357,166 @@
"\n",
"lst[-5:]"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>e_id</th>\n",
" <th>n_disrupt_sample</th>\n",
" <th>total_n_disrupt_firm_prod_experiment</th>\n",
" <th>dct_lst_init_disrupt_firm_prod</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>383</td>\n",
" <td>50</td>\n",
" <td>300.0</td>\n",
" <td>b'\\x80\\x05\\x95\\x17\\x00\\x00\\x00\\x00\\x00\\x00\\x00...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>227</td>\n",
" <td>50</td>\n",
" <td>250.0</td>\n",
" <td>b'\\x80\\x05\\x95\\x16\\x00\\x00\\x00\\x00\\x00\\x00\\x00...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>83</td>\n",
" <td>50</td>\n",
" <td>200.0</td>\n",
" <td>b'\\x80\\x05\\x95\\x16\\x00\\x00\\x00\\x00\\x00\\x00\\x00...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>135</td>\n",
" <td>50</td>\n",
" <td>200.0</td>\n",
" <td>b'\\x80\\x05\\x95\\x16\\x00\\x00\\x00\\x00\\x00\\x00\\x00...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>179</td>\n",
" <td>50</td>\n",
" <td>200.0</td>\n",
" <td>b'\\x80\\x05\\x95\\x16\\x00\\x00\\x00\\x00\\x00\\x00\\x00...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>90</th>\n",
" <td>76</td>\n",
" <td>24</td>\n",
" <td>56.0</td>\n",
" <td>b'\\x80\\x05\\x95\\x14\\x00\\x00\\x00\\x00\\x00\\x00\\x00...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>91</th>\n",
" <td>89</td>\n",
" <td>24</td>\n",
" <td>54.0</td>\n",
" <td>b'\\x80\\x05\\x95\\x16\\x00\\x00\\x00\\x00\\x00\\x00\\x00...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>92</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>54.0</td>\n",
" <td>b'\\x80\\x05\\x95\\x16\\x00\\x00\\x00\\x00\\x00\\x00\\x00...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93</th>\n",
" <td>335</td>\n",
" <td>24</td>\n",
" <td>54.0</td>\n",
" <td>b'\\x80\\x05\\x95\\x17\\x00\\x00\\x00\\x00\\x00\\x00\\x00...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>94</th>\n",
" <td>449</td>\n",
" <td>24</td>\n",
" <td>53.0</td>\n",
" <td>b'\\x80\\x05\\x95\\x15\\x00\\x00\\x00\\x00\\x00\\x00\\x00...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>95 rows × 4 columns</p>\n",
"</div>"
],
"text/plain": [
" e_id n_disrupt_sample total_n_disrupt_firm_prod_experiment \\\n",
"0 383 50 300.0 \n",
"1 227 50 250.0 \n",
"2 83 50 200.0 \n",
"3 135 50 200.0 \n",
"4 179 50 200.0 \n",
".. ... ... ... \n",
"90 76 24 56.0 \n",
"91 89 24 54.0 \n",
"92 90 24 54.0 \n",
"93 335 24 54.0 \n",
"94 449 24 53.0 \n",
"\n",
" dct_lst_init_disrupt_firm_prod \n",
"0 b'\\x80\\x05\\x95\\x17\\x00\\x00\\x00\\x00\\x00\\x00\\x00... \n",
"1 b'\\x80\\x05\\x95\\x16\\x00\\x00\\x00\\x00\\x00\\x00\\x00... \n",
"2 b'\\x80\\x05\\x95\\x16\\x00\\x00\\x00\\x00\\x00\\x00\\x00... \n",
"3 b'\\x80\\x05\\x95\\x16\\x00\\x00\\x00\\x00\\x00\\x00\\x00... \n",
"4 b'\\x80\\x05\\x95\\x16\\x00\\x00\\x00\\x00\\x00\\x00\\x00... \n",
".. ... \n",
"90 b'\\x80\\x05\\x95\\x14\\x00\\x00\\x00\\x00\\x00\\x00\\x00... \n",
"91 b'\\x80\\x05\\x95\\x16\\x00\\x00\\x00\\x00\\x00\\x00\\x00... \n",
"92 b'\\x80\\x05\\x95\\x16\\x00\\x00\\x00\\x00\\x00\\x00\\x00... \n",
"93 b'\\x80\\x05\\x95\\x17\\x00\\x00\\x00\\x00\\x00\\x00\\x00... \n",
"94 b'\\x80\\x05\\x95\\x15\\x00\\x00\\x00\\x00\\x00\\x00\\x00... \n",
"\n",
"[95 rows x 4 columns]"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"with open('SQL_export_high_risk_setting.sql', 'r') as f:\n",
" contents = f.read()\n",
"\n",
"import pandas as pd\n",
"from orm import engine\n",
"result = pd.read_sql(sql=contents, con=engine)\n",
"result"
]
}
],
"metadata": {