{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "e08ec366", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd \n", "from matplotlib import pyplot as plt" ] }, { "cell_type": "markdown", "id": "6f17ee96", "metadata": {}, "source": [ "# Импорт" ] }, { "cell_type": "code", "execution_count": 2, "id": "38906a0f", "metadata": {}, "outputs": [], "source": [ "table = pd.read_csv(\"../results/test_processing_camera1-2020-10-14---19-38-42---093390448_scaled.txt\", sep=\" \")" ] }, { "cell_type": "code", "execution_count": 3, "id": "229279d5", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
0.08582220.011983-0.170964-0.00410493
00.0867060.0114441-0.172755-0.00463303
10.0883080.0108745-0.175963-0.00552038
20.0894970.00701769-0.178534-0.00543287
30.0899540.00853847-0.179394-0.00493487
40.0914400.00858735-0.182333-0.0056773
.........
59650.171849-0.194806-0.237777-0.149945
59660.172449-0.195018-0.239285-0.149969
59670.172471-0.196777-0.237949-0.149896
59680.173594-0.198954-0.238975-0.150473
59690.171928-0.195619-0.23765-0.149442
\n", "

5970 rows × 2 columns

\n", "
" ], "text/plain": [ " 0.0858222 0.011983-0.170964-0.00410493\n", "0 0.086706 0.0114441-0.172755-0.00463303\n", "1 0.088308 0.0108745-0.175963-0.00552038\n", "2 0.089497 0.00701769-0.178534-0.00543287\n", "3 0.089954 0.00853847-0.179394-0.00493487\n", "4 0.091440 0.00858735-0.182333-0.0056773\n", "... ... ...\n", "5965 0.171849 -0.194806-0.237777-0.149945\n", "5966 0.172449 -0.195018-0.239285-0.149969\n", "5967 0.172471 -0.196777-0.237949-0.149896\n", "5968 0.173594 -0.198954-0.238975-0.150473\n", "5969 0.171928 -0.195619-0.23765-0.149442\n", "\n", "[5970 rows x 2 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "table" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.8.10" } }, "nbformat": 4, "nbformat_minor": 5 }