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a62b24ac1cb3ead25d05c19a9f0c0a1d9638bb80
aiomql/Untitled1.ipynb
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Ichinga Samuel a62b24ac1c testdata
2024-08-29 06:36:09 +01:00

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "f1039720-9692-4605-adf9-d37651958e4c",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"from pandas import DataFrame, Series"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "8d39819f-2cac-437f-b5fc-633ca7443f8a",
"metadata": {},
"outputs": [],
"source": [
"rs = DataFrame({0: range(10, 101, 10), 1: range(10, 20), 2: range(20, 40, 2), \"symbols\": [chr(i) for i in [65]*5 + [68]*5]})"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "d7976bb8-05cb-4924-a6e2-90ea8af85d9d",
"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>0</th>\n",
" <th>1</th>\n",
" <th>2</th>\n",
" <th>symbols</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>10</td>\n",
" <td>10</td>\n",
" <td>20</td>\n",
" <td>A</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>20</td>\n",
" <td>11</td>\n",
" <td>22</td>\n",
" <td>A</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>30</td>\n",
" <td>12</td>\n",
" <td>24</td>\n",
" <td>A</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>40</td>\n",
" <td>13</td>\n",
" <td>26</td>\n",
" <td>A</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>50</td>\n",
" <td>14</td>\n",
" <td>28</td>\n",
" <td>A</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0 1 2 symbols\n",
"0 10 10 20 A\n",
"1 20 11 22 A\n",
"2 30 12 24 A\n",
"3 40 13 26 A\n",
"4 50 14 28 A"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rs[rs.symbols == 'A']"
]
},
{
"cell_type": "code",
"execution_count": 71,
"id": "eb69c292-79e3-4105-b10c-6f4f5c22074f",
"metadata": {},
"outputs": [
{
"ename": "KeyError",
"evalue": "None",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[1;32mIn[71], line 2\u001b[0m\n\u001b[0;32m 1\u001b[0m ind \u001b[38;5;241m=\u001b[39m rs[rs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124msymbols\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mA\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39miloc[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;241m.\u001b[39mname\n\u001b[1;32m----> 2\u001b[0m \u001b[43mrs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloc\u001b[49m\u001b[43m[\u001b[49m\u001b[43mind\u001b[49m\u001b[43m]\u001b[49m\n",
"File \u001b[1;32m~\\OneDrive - UBA\\Documents\\Personal\\VS\\aiomql\\venv\\Lib\\site-packages\\pandas\\core\\indexing.py:1191\u001b[0m, in \u001b[0;36m_LocationIndexer.__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m 1189\u001b[0m maybe_callable \u001b[38;5;241m=\u001b[39m com\u001b[38;5;241m.\u001b[39mapply_if_callable(key, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj)\n\u001b[0;32m 1190\u001b[0m maybe_callable \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_deprecated_callable_usage(key, maybe_callable)\n\u001b[1;32m-> 1191\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_axis\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmaybe_callable\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[1;32m~\\OneDrive - UBA\\Documents\\Personal\\VS\\aiomql\\venv\\Lib\\site-packages\\pandas\\core\\indexing.py:1431\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_axis\u001b[1;34m(self, key, axis)\u001b[0m\n\u001b[0;32m 1429\u001b[0m \u001b[38;5;66;03m# fall thru to straight lookup\u001b[39;00m\n\u001b[0;32m 1430\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_key(key, axis)\n\u001b[1;32m-> 1431\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_label\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[1;32m~\\OneDrive - UBA\\Documents\\Personal\\VS\\aiomql\\venv\\Lib\\site-packages\\pandas\\core\\indexing.py:1381\u001b[0m, in \u001b[0;36m_LocIndexer._get_label\u001b[1;34m(self, label, axis)\u001b[0m\n\u001b[0;32m 1379\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_get_label\u001b[39m(\u001b[38;5;28mself\u001b[39m, label, axis: AxisInt):\n\u001b[0;32m 1380\u001b[0m \u001b[38;5;66;03m# GH#5567 this will fail if the label is not present in the axis.\u001b[39;00m\n\u001b[1;32m-> 1381\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mobj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mxs\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlabel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[1;32m~\\OneDrive - UBA\\Documents\\Personal\\VS\\aiomql\\venv\\Lib\\site-packages\\pandas\\core\\generic.py:4301\u001b[0m, in \u001b[0;36mNDFrame.xs\u001b[1;34m(self, key, axis, level, drop_level)\u001b[0m\n\u001b[0;32m 4299\u001b[0m new_index \u001b[38;5;241m=\u001b[39m index[loc]\n\u001b[0;32m 4300\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m-> 4301\u001b[0m loc \u001b[38;5;241m=\u001b[39m \u001b[43mindex\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 4303\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(loc, np\u001b[38;5;241m.\u001b[39mndarray):\n\u001b[0;32m 4304\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m loc\u001b[38;5;241m.\u001b[39mdtype \u001b[38;5;241m==\u001b[39m np\u001b[38;5;241m.\u001b[39mbool_:\n",
"File \u001b[1;32m~\\OneDrive - UBA\\Documents\\Personal\\VS\\aiomql\\venv\\Lib\\site-packages\\pandas\\core\\indexes\\range.py:417\u001b[0m, in \u001b[0;36mRangeIndex.get_loc\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m 415\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[0;32m 416\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(key, Hashable):\n\u001b[1;32m--> 417\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key)\n\u001b[0;32m 418\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_indexing_error(key)\n\u001b[0;32m 419\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key)\n",
"\u001b[1;31mKeyError\u001b[0m: None"
]
}
],
"source": [
"ind = rs[rs['symbols'] != 'A'].iloc[0].index.name\n",
"rs.loc[ind]"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "cce9fa9e-d841-4f45-8813-313f17e7b12f",
"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>0</th>\n",
" <th>1</th>\n",
" <th>2</th>\n",
" <th>symbols</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>10</td>\n",
" <td>10</td>\n",
" <td>20</td>\n",
" <td>A</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>20</td>\n",
" <td>11</td>\n",
" <td>22</td>\n",
" <td>A</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>30</td>\n",
" <td>12</td>\n",
" <td>24</td>\n",
" <td>A</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>40</td>\n",
" <td>13</td>\n",
" <td>26</td>\n",
" <td>A</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>50</td>\n",
" <td>14</td>\n",
" <td>28</td>\n",
" <td>A</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>60</td>\n",
" <td>15</td>\n",
" <td>30</td>\n",
" <td>D</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>70</td>\n",
" <td>16</td>\n",
" <td>32</td>\n",
" <td>D</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>80</td>\n",
" <td>17</td>\n",
" <td>34</td>\n",
" <td>D</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>90</td>\n",
" <td>18</td>\n",
" <td>36</td>\n",
" <td>D</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>100</td>\n",
" <td>19</td>\n",
" <td>38</td>\n",
" <td>D</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0 1 2 symbols\n",
"0 10 10 20 A\n",
"1 20 11 22 A\n",
"2 30 12 24 A\n",
"3 40 13 26 A\n",
"4 50 14 28 A\n",
"5 60 15 30 D\n",
"6 70 16 32 D\n",
"7 80 17 34 D\n",
"8 90 18 36 D\n",
"9 100 19 38 D"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rs"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "3c456100-4931-4fbd-a63d-531eaf735e70",
"metadata": {},
"outputs": [
{
"ename": "InvalidIndexError",
"evalue": "RangeIndex(start=0, stop=10, step=1)",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mInvalidIndexError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[1;32mIn[31], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mrs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mindex\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrs\u001b[49m\u001b[43m[\u001b[49m\u001b[43mrs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mindex\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m<\u001b[39;49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m31\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mindex\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[1;32m~\\OneDrive - UBA\\Documents\\Personal\\VS\\aiomql\\venv\\Lib\\site-packages\\pandas\\core\\indexes\\range.py:418\u001b[0m, in \u001b[0;36mRangeIndex.get_loc\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m 416\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(key, Hashable):\n\u001b[0;32m 417\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key)\n\u001b[1;32m--> 418\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_check_indexing_error\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 419\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key)\n",
"File \u001b[1;32m~\\OneDrive - UBA\\Documents\\Personal\\VS\\aiomql\\venv\\Lib\\site-packages\\pandas\\core\\indexes\\base.py:6059\u001b[0m, in \u001b[0;36mIndex._check_indexing_error\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m 6055\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_check_indexing_error\u001b[39m(\u001b[38;5;28mself\u001b[39m, key):\n\u001b[0;32m 6056\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m is_scalar(key):\n\u001b[0;32m 6057\u001b[0m \u001b[38;5;66;03m# if key is not a scalar, directly raise an error (the code below\u001b[39;00m\n\u001b[0;32m 6058\u001b[0m \u001b[38;5;66;03m# would convert to numpy arrays and raise later any way) - GH29926\u001b[39;00m\n\u001b[1;32m-> 6059\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m InvalidIndexError(key)\n",
"\u001b[1;31mInvalidIndexError\u001b[0m: RangeIndex(start=0, stop=10, step=1)"
]
}
],
"source": [
"rs.index.get_loc(rs[rs.index <= 31].index)"
]
},
{
"cell_type": "code",
"execution_count": 73,
"id": "1a5a99bb-3fc4-458d-95b8-4e031f3e04c1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index([20, 22, 24, 26, 28, 30, 32, 34, 36, 38], dtype='int64', name=2)"
]
},
"execution_count": 73,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rs.index"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "2d53ccef-72e1-4378-818f-b60682bbd8b7",
"metadata": {},
"outputs": [],
"source": [
"g = rs[rs.index <= 31].iloc[-1]"
]
},
{
"cell_type": "code",
"execution_count": 87,
"id": "7318351e-e185-4695-ada5-43596b4844e6",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"np.int64(20)"
]
},
"execution_count": 87,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rs.index[0]"
]
},
{
"cell_type": "code",
"execution_count": 114,
"id": "55441116-8c00-4fd1-94c8-939320c6dfc4",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[25, 26, 27, 28, 29]"
]
},
"execution_count": 114,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t = list(range(30))\n",
"t[25:30]"
]
},
{
"cell_type": "code",
"execution_count": 121,
"id": "6ef28e4c-15a5-4fe5-aa66-10ba464f1256",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[6, 7, 8, 9]"
]
},
"execution_count": 121,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t[6: 10]"
]
},
{
"cell_type": "code",
"execution_count": 126,
"id": "f15cf18c-54cb-4624-8d18-3998bde2b9ba",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"None\n"
]
}
],
"source": [
"p = 0 or None\n",
"print(p)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "47dd4064-dde6-4824-a12b-ecf334bf4ebe",
"metadata": {},
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}
],
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},
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