Spaces:
Build error
Build error
File size: 4,896 Bytes
36eb7b3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 |
{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 5,
"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>nrishit</th>\n",
" <th>05:45:39:PM</th>\n",
" <th>17-February-2024nrishit</th>\n",
" <th>05:45:40:PM</th>\n",
" <th>17-February-2024nrishit.1</th>\n",
" <th>05:45:41:PM</th>\n",
" <th>17-February-2024nrishit.2</th>\n",
" <th>05:45:41:PM.1</th>\n",
" <th>17-February-2024nrishit.3</th>\n",
" <th>05:45:42:PM</th>\n",
" <th>...</th>\n",
" <th>05:51:20:PM.11</th>\n",
" <th>17-February-2024nsakshi.388</th>\n",
" <th>05:51:20:PM.12</th>\n",
" <th>17-February-2024nanshika.282</th>\n",
" <th>05:51:20:PM.13</th>\n",
" <th>17-February-2024nsakshi.389</th>\n",
" <th>05:51:20:PM.14</th>\n",
" <th>17-February-2024nsakshi.390</th>\n",
" <th>05:51:20:PM.15</th>\n",
" <th>17-February-2024</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" </tbody>\n",
"</table>\n",
"<p>0 rows Γ 1659 columns</p>\n",
"</div>"
],
"text/plain": [
"Empty DataFrame\n",
"Columns: [nrishit, 05:45:39:PM, 17-February-2024nrishit, 05:45:40:PM, 17-February-2024nrishit.1, 05:45:41:PM, 17-February-2024nrishit.2, 05:45:41:PM.1, 17-February-2024nrishit.3, 05:45:42:PM, 17-February-2024nrishit.4, 05:45:42:PM.1, 17-February-2024nrishit.5, 05:45:43:PM, 17-February-2024nrishit.6, 05:45:44:PM, 17-February-2024nrishit.7, 05:45:44:PM.1, 17-February-2024nsakshi, 05:45:48:PM, 17-February-2024nsakshi.1, 05:45:49:PM, 17-February-2024nsakshi.2, 05:45:49:PM.1, 17-February-2024nsakshi.3, 05:45:49:PM.2, 17-February-2024nsakshi.4, 05:45:50:PM, 17-February-2024nsakshi.5, 05:45:51:PM, 17-February-2024nsakshi.6, 05:45:51:PM.1, 17-February-2024nsakshi.7, 05:45:52:PM, 17-February-2024nsakshi.8, 05:45:53:PM, 17-February-2024nsakshi.9, 05:45:53:PM.1, 17-February-2024nsakshi.10, 05:45:54:PM, 17-February-2024nsakshi.11, 05:45:55:PM, 17-February-2024nrishit.8, 05:45:55:PM.1, 17-February-2024nrishit.9, 05:45:55:PM.2, 17-February-2024nrishit.10, 05:45:56:PM, 17-February-2024nrishit.11, 05:45:57:PM, 17-February-2024nrishit.12, 05:45:57:PM.1, 17-February-2024nrishit.13, 05:45:58:PM, 17-February-2024nrishit.14, 05:45:59:PM, 17-February-2024nrishit.15, 05:45:59:PM.1, 17-February-2024nrishit.16, 05:46:00:PM, 17-February-2024nrishit.17, 05:46:01:PM, 17-February-2024nrishit.18, 05:46:03:PM, 17-February-2024nrishit.19, 05:46:03:PM.1, 17-February-2024nrishit.20, 05:46:05:PM, 17-February-2024nsakshi.12, 05:46:05:PM.1, 17-February-2024nrishit.21, 05:46:05:PM.2, 17-February-2024nrishit.22, 05:46:08:PM, 17-February-2024nrishit.23, 05:46:09:PM, 17-February-2024nrishit.24, 05:50:27:PM, 17-February-2024nrishit.25, 05:50:27:PM.1, 17-February-2024nsakshi.13, 05:50:27:PM.2, 17-February-2024nrishit.26, 05:50:27:PM.3, 17-February-2024nrishit.27, 05:50:27:PM.4, 17-February-2024nsakshi.14, 05:50:27:PM.5, 17-February-2024nsakshi.15, 05:50:27:PM.6, 17-February-2024nrishit.28, 05:50:27:PM.7, 17-February-2024nsakshi.16, 05:50:27:PM.8, 17-February-2024nrishit.29, 05:50:27:PM.9, 17-February-2024nrishit.30, 05:50:27:PM.10, 17-February-2024nsakshi.17, 05:50:27:PM.11, ...]\n",
"Index: []\n",
"\n",
"[0 rows x 1659 columns]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.read_csv('Attendance.csv')\n",
"df.head()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.18"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
|