Georg_Brantegger/Python-DT_Slot_3
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity
Files
137182ab10bc91be76ce1daf3a4653c46b9646f2
Python-DT_Slot_3/Validation Data/sighting_validation_data.ipynb
Georg ´Brantegger 137182ab10 working on data validation
2022-09-14 15:13:44 +02:00

133 lines
41 KiB
Plaintext
Raw Blame History

{
"cells": [
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import time\n",
"from datetime import datetime\n",
"import matplotlib.pyplot as plt\n"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\georg\\AppData\\Local\\Temp\\ipykernel_34540\\1340824978.py:1: ParserWarning: Length of header or names does not match length of data. This leads to a loss of data with index_col=False.\n",
" raw_data = pd.read_csv(\"2015_08_24 18.00 M1 SS100%.csv\",sep=\";\",header=7,index_col=False)\n"
]
}
],
"source": [
"raw_data = pd.read_csv(\"2015_08_24 18.00 M1 SS100%.csv\",sep=\";\",header=7,index_col=False)\n",
"raw_data.replace({',': '.'}, regex=True,inplace=True)\n",
"time_format = \"%m/%d/%Y %I:%M:%S.%f %p\"\n",
"\n",
"col_names = ['timestamp','M1-LA','M2-LA','Druck']\n",
"df = pd.DataFrame(columns=col_names)\n",
"\n",
"df['timestamp'] = pd.to_datetime(raw_data[\"Date/Time\"],format=time_format).astype(np.int64)/10**9\n",
"df['M1-LA'] = pd.to_numeric(raw_data['M1-LA'])/100\n",
"df['M2-LA'] = pd.to_numeric(raw_data['M2-LA'])/100\n",
"df['Druck'] = pd.to_numeric(raw_data['P-DRL'])\n"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"t_vec = np.array(df['timestamp']-df['timestamp'][0])\n",
"LA1_vec = np.array(df['M1-LA']) \n",
"LA2_vec = np.array(df['M2-LA'])\n",
"p_vec = np.array(df['Druck']) "
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x1f774d49760>]"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "9c2016ba1ceb4d07a17a483bbf50f9a6",
"version_major": 2,
"version_minor": 0
},
"image/png": "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",
"text/html": [
"\n",
" <div style=\"display: inline-block;\">\n",
" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
" Figure\n",
" </div>\n",
" <img src='data:image/png;base64,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' width=640.0/>\n",
" </div>\n",
" "
],
"text/plain": [
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib widget\n",
"\n",
"plt.plot(t_vec,LA1_vec)\n",
"plt.plot(t_vec,LA2_vec)\n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.8.13 ('DT_Slot_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": "3.8.13"
},
"orig_nbformat": 4,
"vscode": {
"interpreter": {
"hash": "4a28055eb8a3160fa4c7e4fca69770c4e0a1add985300856aa3fcf4ce32a2c48"
}
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Reference in New Issue View Git Blame Copy Permalink