"D:\\ProgramData\\Anaconda3\\envs\\alpha-mind\\lib\\site-packages\\alpha_mind-0.2.3-py3.7-win-amd64.egg\\alphamind\\model\\data_preparing.py:412: FutureWarning: DataFrame.mean and DataFrame.median with numeric_only=None will include datetime64 and datetime64tz columns in a future version.\n",
"D:\\ProgramData\\Anaconda3\\envs\\alpha-mind\\lib\\site-packages\\alpha_mind-0.2.3-py3.7-win-amd64.egg\\alphamind\\model\\data_preparing.py:412: FutureWarning: DataFrame.mean and DataFrame.median with numeric_only=None will include datetime64 and datetime64tz columns in a future version.\n",
" lambda x: x.fillna(x.median())).reset_index(\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Const. Testing IC: -0.1104\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"D:\\ProgramData\\Anaconda3\\envs\\alpha-mind\\lib\\site-packages\\alpha_mind-0.2.3-py3.7-win-amd64.egg\\alphamind\\model\\data_preparing.py:412: FutureWarning: DataFrame.mean and DataFrame.median with numeric_only=None will include datetime64 and datetime64tz columns in a future version.\n",
"D:\\ProgramData\\Anaconda3\\envs\\alpha-mind\\lib\\site-packages\\alpha_mind-0.2.3-py3.7-win-amd64.egg\\alphamind\\model\\data_preparing.py:412: FutureWarning: DataFrame.mean and DataFrame.median with numeric_only=None will include datetime64 and datetime64tz columns in a future version.\n",
" lambda x: x.fillna(x.median())).reset_index(\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"2020-01-02 Const. Testing IC: 0.1702\n",
"2020-01-02 Regression Testing IC: 0.1703\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"D:\\ProgramData\\Anaconda3\\envs\\alpha-mind\\lib\\site-packages\\alpha_mind-0.2.3-py3.7-win-amd64.egg\\alphamind\\model\\data_preparing.py:412: FutureWarning: DataFrame.mean and DataFrame.median with numeric_only=None will include datetime64 and datetime64tz columns in a future version.\n",
" lambda x: x.fillna(x.median())).reset_index(\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"2020-01-16 Const. Testing IC: 0.1982\n",
"2020-01-16 Regression Testing IC: -0.2011\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"D:\\ProgramData\\Anaconda3\\envs\\alpha-mind\\lib\\site-packages\\alpha_mind-0.2.3-py3.7-win-amd64.egg\\alphamind\\model\\data_preparing.py:412: FutureWarning: DataFrame.mean and DataFrame.median with numeric_only=None will include datetime64 and datetime64tz columns in a future version.\n",
" lambda x: x.fillna(x.median())).reset_index(\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"2020-02-07 Const. Testing IC: 0.0492\n",
"2020-02-07 Regression Testing IC: 0.0469\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"D:\\ProgramData\\Anaconda3\\envs\\alpha-mind\\lib\\site-packages\\alpha_mind-0.2.3-py3.7-win-amd64.egg\\alphamind\\model\\data_preparing.py:412: FutureWarning: DataFrame.mean and DataFrame.median with numeric_only=None will include datetime64 and datetime64tz columns in a future version.\n",
"\u001b[1;32m<ipython-input-2-f2d6467b9b29>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdx_return_data\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
" }\n",
"\u001b[1;31mNameError\u001b[0m: name 'dx_return_data' is not defined"
"\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>trade_date</th>\n",
" <th>code</th>\n",
" <th>dx</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2020-01-02</td>\n",
" <td>2010000001</td>\n",
" <td>-0.021890</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2020-01-02</td>\n",
" <td>2010000005</td>\n",
" <td>0.006826</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>2020-01-02</td>\n",
" <td>2010000010</td>\n",
" <td>-0.051323</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>2020-01-02</td>\n",
" <td>2010000011</td>\n",
" <td>-0.015151</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>2020-01-02</td>\n",
" <td>2010000012</td>\n",
" <td>-0.017889</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" trade_date code dx\n",
"0 2020-01-02 2010000001 -0.021890\n",
"4 2020-01-02 2010000005 0.006826\n",
"8 2020-01-02 2010000010 -0.051323\n",
"12 2020-01-02 2010000011 -0.015151\n",
"16 2020-01-02 2010000012 -0.017889"
]
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
}
],
],
"source": [
"source": [
...
@@ -286,18 +500,21 @@
...
@@ -286,18 +500,21 @@
},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count": 3,
"execution_count": 17,
"metadata": {},
"metadata": {},
"outputs": [
"outputs": [
{
{
"ename": "NameError",
"name": "stderr",
"evalue": "name 'model_dates' is not defined",
"output_type": "stream",
"output_type": "error",
"text": [
"traceback": [
"2020-11-22 01:31:22,196 - ALPHA_MIND - INFO - 2020-01-02 full re-balance: 300\n",
