{ "cells": [ { "cell_type": "markdown", "id": "surprising-coordinate", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "# Matematikai Algoritmusok és Felfedezések I.\n", "\n", "## 9. Előadás: Matplotlib\n", "### 2021 április 12." ] }, { "cell_type": "markdown", "id": "healthy-jonathan", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "## Adatvizualizáció \n", "\n", "Fontos, hogy az adatokat informatív módon tudjuk prezentálni mások (és persze magunk) számára. \n", "\n" ] }, { "cell_type": "markdown", "id": "federal-screening", "metadata": {}, "source": [ " $\"Drawing\"$ " ] }, { "cell_type": "code", "execution_count": 1, "id": "raising-intention", "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [], "source": [ "import numpy as np\n", "import random as rn\n", "import matplotlib.pyplot as plt\n", "import csv # csv fájlból fogunk beolvasni adatokat. \n" ] }, { "cell_type": "markdown", "id": "superior-azerbaijan", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "# Matplotlib\n", "- A legismertebb grafikon és ábra készítő Pythonban. \n", "- Példákon keresztül nézzük meg a működését." ] }, { "cell_type": "markdown", "id": "engaged-reply", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "# New Yorki mókusok\n", "Az adatok egy csv (comma separated values) fájlban vannak, a honlapon megtalálható. Minden sor egy mókus észlelés adatait írja le a Central Parkban. Az első sorból látszik, hogy milyen adatok vannak megadva észlelésenként: \n", "\n", "long,lat,unique_squirrel_id,hectare,shift,date,hectare_squirrel_number,age,primary_fur_color,highlight_fur_color,\n", "combination_of_primary_and_highlight_color,color_notes,location,above_ground_sighter_measurement,specific_location,running,\n", "chasing,climbing,eating,foraging,other_activities,kuks,quaas,moans,tail_flags,tail_twitches,approaches,indifferent,runs_from,\n", "other_interactions,lat_long,zip_codes,community_districts,borough_boundaries,city_council_districts,police_precincts\n", "\n", "Először készítünk egy függvényt, ami beolvas egy oszlopot:" ] }, { "cell_type": "code", "execution_count": 2, "id": "ahead-hawaii", "metadata": {}, "outputs": [], "source": [ "def getcolumn(fajlnev, ind): # egy oszlop beolvasása egy cvs fájlból, de legfeljebb 3000 elem. \n", " ans=[]\n", " c=0\n", " with open(fajlnev, newline='') as csvfile:\n", " sqreader = csv.reader(csvfile, delimiter=',', quotechar='\"')\n", " ans=[next(sqreader)[ind] for _ in range(3000)]\n", " del ans[0]\n", " return ans\n", " return ans " ] }, { "cell_type": "code", "execution_count": 3, "id": "authentic-miami", "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "data": { "text/plain": [ "['NA',\n", " 'Adult',\n", " 'Adult',\n", " 'Juvenile',\n", " 'NA',\n", " 'Juvenile',\n", " 'Adult',\n", " 'NA',\n", " 'Adult',\n", " 'Adult']" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "getcolumn('nyc_squirrels.csv',7)[0:10] # első 10 mókus kora" ] }, { "cell_type": "code", "execution_count": 4, "id": "dressed-elements", "metadata": {}, "outputs": [], "source": [ "a=getcolumn('nyc_squirrels.csv',7)\n", "num=np.array(a)\n", "unique, counts = np.unique(num, return_counts=True) # A tömbben előforduló egyedei objektumok és hogy hányszor \n", " # fordulnak elő" ] }, { "cell_type": "code", "execution_count": 5, "id": "social-farming", "metadata": { "scrolled": true, "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['?' 'Adult' 'Juvenile' 'NA']\n", "[ 4 2550 327 118]\n" ] } ], "source": [ "print(unique)\n", "print(counts)" ] }, { "cell_type": "code", "execution_count": 6, "id": "assured-danish", "metadata": {}, "outputs": [ { "data": { "image/png": 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iYHenyWuAP62q1w3rfmqcL2AWXAi8I8kLd7Ls7Yx+z8EVjO+sY8bMu6/57S2SPAe4BHhTVf1ojqczE1YCfzfcXzc8fhlwAUBV3Zzk5jma26wa/n7t1cDvJPkc8GbgL4HfYPTbnv4tCcB+wLfbpl8Ybm8A3jrR/oejy18HPjvsB0ZnIHuNqno0yeXAnwE//R/e8JnzQ1X1X0m2AWuTHFxVD8/VXHfHKE7di4BHqurOuZ7IuCU5GPhN4NVJitHnQQX8+y4263+365dmcHoz6Ul+9uypv451wFnAw8Cmqnoso4JtrKqJjn6eGG6fYtd/1p4D/Kiqlk1p1vPH3wI3Av/UxlYCr0hyz/D4l4HfAy6e1ZntAU+fp+6HwAfnehIz5G3Ap6vqJVW1uKoWAXczOuL5A4Akvwr8WtvmgSSvHI6g3zLBfh8DXjCD856ue4GlSfZPciBwXFv2deBI4I8ZBRLgOuD1SV4GkOT5SV6+p09aVY8Cdyf5/WE/SfKaqb+MuTEc/V3J6HPoHWdTpwKvHv47WszoY5l5fQptFKfuhcAfzfUkZshK4KpnjH0eOAI4IMntwMcYRXKH1cCXGF2Nv3+C/V4K/MN8u9CSZF/giaq6j9Ef6luH258eGVfVU4xe30nDLVW1ndEV9SuGjxK+DUz1Ask7gDOS/Aewmb3ggsQEzmf023EA3ghsq6r/bsu/weh/PIfN+swmyW+06BfecFR2cVUdNddz0dzzSFG/0JK8j9FV0Y/O9Vw0P3ikKEmNR4qS1BhFSWqMoiQ1RlGSGqMoSY1RlKTm/wEZ1/2ZyYBmTAAAAABJRU5ErkJggg==\n", 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