{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Praktikumi nimi" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Tudengi Nimi \n", "Kuupäev \n", "jne" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# laadime vajalikud töövahendid\n", "# see lahter tuleb alati esimesena käivitada töölehe avamisel\n", "import numpy as np\n", "from numpy import sqrt, exp, log, sin, cos, tan, polyfit\n", "from scipy.optimize import curve_fit\n", "import pandas as pd\n", "pd.set_option('display.max_rows', 20)\n", "from matplotlib.pyplot import *\n", "from matplotlib import rcParams\n", "rcParams['figure.dpi'] = 100\n", "rcParams['lines.markersize'] = 4\n", "rcParams['font.size'] = 12\n", "rcParams['axes.prop_cycle'] = cycler('color', 'brgmyk')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Eksperimendi kirjeldus" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Siia võiks midagi kirjutada ..." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Katseandmed" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Avades andmefaili tekstiredaktoriga, näeme et esimesed 7 rida andmeid ei sisalda, kümnenderaldaja on koma, andmetulpasid on 4 tükki ja need on eraldatud tabulatsioonisümboliga. Selliste andmete lugemiseks sobib `pandas.read_table` (veidi lihtsamaid andmeid võiks lugeda ka funktsiooniga `numpy.loadtxt`).\n", "\n", "(Mistahes funktsiooni kohta lisainfo saamiseks guugelda vastavaid märksõnu, näiteks `pandas read_table`.)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | t | \n", "T1 | \n", "T2 | \n", "T3 | \n", "
---|---|---|---|---|
1 | \n", "0.0 | \n", "22.1 | \n", "22.0 | \n", "22.9 | \n", "
2 | \n", "0.5 | \n", "22.1 | \n", "22.0 | \n", "23.0 | \n", "
3 | \n", "1.0 | \n", "22.2 | \n", "22.0 | \n", "23.1 | \n", "
4 | \n", "1.5 | \n", "22.3 | \n", "22.1 | \n", "23.2 | \n", "
5 | \n", "2.0 | \n", "22.3 | \n", "22.1 | \n", "23.2 | \n", "
6 | \n", "2.5 | \n", "22.4 | \n", "22.2 | \n", "23.3 | \n", "
7 | \n", "3.0 | \n", "22.4 | \n", "22.3 | \n", "23.4 | \n", "
8 | \n", "3.5 | \n", "22.5 | \n", "22.4 | \n", "23.5 | \n", "
9 | \n", "4.0 | \n", "22.6 | \n", "22.5 | \n", "23.5 | \n", "
10 | \n", "4.5 | \n", "22.6 | \n", "22.6 | \n", "23.6 | \n", "
... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
472 | \n", "235.5 | \n", "72.7 | \n", "46.8 | \n", "66.6 | \n", "
473 | \n", "236.0 | \n", "72.8 | \n", "46.8 | \n", "66.6 | \n", "
474 | \n", "236.5 | \n", "72.9 | \n", "46.8 | \n", "66.7 | \n", "
475 | \n", "237.0 | \n", "73.0 | \n", "46.8 | \n", "66.7 | \n", "
476 | \n", "237.5 | \n", "73.2 | \n", "46.9 | \n", "66.8 | \n", "
477 | \n", "238.0 | \n", "73.3 | \n", "46.9 | \n", "66.8 | \n", "
478 | \n", "238.5 | \n", "73.4 | \n", "47.0 | \n", "66.9 | \n", "
479 | \n", "239.0 | \n", "73.5 | \n", "47.0 | \n", "66.9 | \n", "
480 | \n", "239.5 | \n", "73.5 | \n", "47.1 | \n", "67.0 | \n", "
481 | \n", "240.0 | \n", "73.7 | \n", "47.1 | \n", "67.1 | \n", "
481 rows × 4 columns
\n", "