Matplotlib nuqtali diagramma (scatter)

Tarqalgan chizmalarni yaratish

Pyplot yordamida siz scatter() funksiyasidan scatter chizmasini chizishingiz mumkin.

scatter() funksiyasi har bir kuzatish uchun bitta nuqta chizadi. Unga bir xil uzunlikdagi ikkita massiv kerak bo‘ladi, biri x o‘qi qiymatlari uchun, ikkinchisi esa y o‘qidagi qiymatlar uchun:

Misol

Oddiy nuqtali diagramma (scatter plot):

import matplotlib.pyplot as plt import numpy as np x = np.array([5,7,8,7,2,17,2,9,4,11,12,9,6]) y = np.array([99,86,87,88,111,86,103,87,94,78,77,85,86]) plt.scatter(x, y) plt.show()

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Yuqoridagi misoldagi kuzatuv 13 ta mashinaning o‘tib ketishi natijasidir.

X o‘qi mashinaning qancha eski ekanligini ko‘rsatadi.

Y o‘qi avtomobilning o‘tayotganda tezligini ko‘rsatadi.

Kuzatishlar o‘rtasida bog‘liqlik bormi?

Aftidan, mashina qanchalik yangi bo‘lsa, u shunchalik tez haydaydi, ammo bu tasodif bo‘lishi mumkin, axir biz atigi 13 ta mashinani ro‘yxatdan o‘tkazdik.

Plotlarni solishtiring

Yuqoridagi misolda tezlik va yosh o‘rtasida bog‘liqlik borga o‘xshaydi, ammo kuzatuvlarni boshqa kundan boshlab ham chizsak nima bo‘ladi? Tarqalish syujeti bizga yana bir narsani aytib beradimi?

Misol

Xuddi shu rasmga ikkita chizma chizing:

import matplotlib.pyplot as plt import numpy as np #day one, the age and speed of 13 cars: x = np.array([5,7,8,7,2,17,2,9,4,11,12,9,6]) y = np.array([99,86,87,88,111,86,103,87,94,78,77,85,86]) plt.scatter(x, y) #day two, the age and speed of 15 cars: x = np.array([2,2,8,1,15,8,12,9,7,3,11,4,7,14,12]) y = np.array([100,105,84,105,90,99,90,95,94,100,79,112,91,80,85]) plt.scatter(x, y) plt.show()

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Eslatma: Ikki syujet ikki xil rangda chizilgan, sukut bo‘yicha ko‘k va to‘q sariq, ranglarni qanday o‘zgartirishni keyinroq ushbu bobda bilib olasiz.

Ikki syujetni solishtirib, shuni aytish mumkinki, ularning ikkalasi ham bir xil xulosaga keladi: mashina qanchalik yangi bo‘lsa, u shunchalik tez haydaydi.

Ranglar

coloryoki c argumenti bilan har bir tarqalish chizmasi uchun o‘zingizningcolorni o‘rnatishingiz mumkin:

Misol

Markerlarning o‘z rangini o‘rnating:

import matplotlib.pyplot as plt import numpy as np x = np.array([5,7,8,7,2,17,2,9,4,11,12,9,6]) y = np.array([99,86,87,88,111,86,103,87,94,78,77,85,86]) plt.scatter(x, y, color = 'hotpink') x = np.array([2,2,8,1,15,8,12,9,7,3,11,4,7,14,12]) y = np.array([100,105,84,105,90,99,90,95,94,100,79,112,91,80,85]) plt.scatter(x, y, color = '#88c999') plt.show()

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Har bir nuqtani ranglang

Siz hatto c argumenti uchun qiymat sifatida ranglar massividan foydalanib, har bir nuqta uchun ma’lum rangni o‘rnatishingiz mumkin:

Eslatma: Buning uchuncolorargumentidan foydalana olmaysiz, faqat c argumenti.

Misol

Markerlarning o‘z rangini o‘rnating:

import matplotlib.pyplot as plt import numpy as np x = np.array([5,7,8,7,2,17,2,9,4,11,12,9,6]) y = np.array([99,86,87,88,111,86,103,87,94,78,77,85,86]) colors = np.array(["red","green","blue","yellow","pink","black","orange","purple","beige","brown","gray","cyan","magenta"]) plt.scatter(x, y, c=colors) plt.show()

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Rang xaritasi

Matplotlib modulida bir qator mavjud rang xaritalari mavjud.

Rang xaritasi ranglar ro‘yxatiga o‘xshaydi, bu yerda har bir rang 0 dan 100 gacha bo‘lgan qiymatga ega.

Mana rang xaritasiga misol:

Ushbu rang xaritasi "viridis" deb ataladi va siz ko‘rib turganingizdek, u binafsha rang bo‘lgan 0 dan 100 gacha sariq rangga ega.

ColorMap-dan qanday foydalanish kerak

Siz rang xaritasinicmapkalit so‘zi bilan rang xaritasining qiymati bilan belgilashingiz mumkin, bu holda 'viridis' Matplotlib-da mavjud bo‘lgan ichki rang xaritalaridan biri.

Bundan tashqari, siz (0 dan 100 gacha) qiymatlari bo‘lgan massivni yaratishingiz kerak, tarqalish chizmasidagi har bir nuqta uchun bitta qiymat:

Misol

Ranglar massivi yarating va tarqalish chizmasida rang xaritasini belgilang:

import matplotlib.pyplot as plt import numpy as np x = np.array([5,7,8,7,2,17,2,9,4,11,12,9,6]) y = np.array([99,86,87,88,111,86,103,87,94,78,77,85,86]) colors = np.array([0, 10, 20, 30, 40, 45, 50, 55, 60, 70, 80, 90, 100]) plt.scatter(x, y, c=colors, cmap='viridis') plt.show()

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plt.colorbar() operatorini qo‘shish orqali siz rang xaritasini chizmaga kiritishingiz mumkin:

Misol

Haqiqiy rang xaritasini qo‘shing:

import matplotlib.pyplot as plt import numpy as np x = np.array([5,7,8,7,2,17,2,9,4,11,12,9,6]) y = np.array([99,86,87,88,111,86,103,87,94,78,77,85,86]) colors = np.array([0, 10, 20, 30, 40, 45, 50, 55, 60, 70, 80, 90, 100]) plt.scatter(x, y, c=colors, cmap='viridis') plt.colorbar() plt.show()

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Rangli xaritalar mavjud

Siz o‘rnatilgan rang xaritalaridan birini tanlashingiz mumkin:

Name		Reverse
Accent	Try it »	Accent_r	Try it »
Blues	Try it »	Blues_r	Try it »
BrBG	Try it »	BrBG_r	Try it »
BuGn	Try it »	BuGn_r	Try it »
BuPu	Try it »	BuPu_r	Try it »
CMRmap	Try it »	CMRmap_r	Try it »
Dark2	Try it »	Dark2_r	Try it »
GnBu	Try it »	GnBu_r	Try it »
Greens	Try it »	Greens_r	Try it »
Greys	Try it »	Greys_r	Try it »
OrRd	Try it »	OrRd_r	Try it »
Oranges	Try it »	Oranges_r	Try it »
PRGn	Try it »	PRGn_r	Try it »
Paired	Try it »	Paired_r	Try it »
Pastel1	Try it »	Pastel1_r	Try it »
Pastel2	Try it »	Pastel2_r	Try it »
PiYG	Try it »	PiYG_r	Try it »
PuBu	Try it »	PuBu_r	Try it »
PuBuGn	Try it »	PuBuGn_r	Try it »
PuOr	Try it »	PuOr_r	Try it »
PuRd	Try it »	PuRd_r	Try it »
Purples	Try it »	Purples_r	Try it »
RdBu	Try it »	RdBu_r	Try it »
RdGy	Try it »	RdGy_r	Try it »
RdPu	Try it »	RdPu_r	Try it »
RdYlBu	Try it »	RdYlBu_r	Try it »
RdYlGn	Try it »	RdYlGn_r	Try it »
Reds	Try it »	Reds_r	Try it »
Set1	Try it »	Set1_r	Try it »
Set2	Try it »	Set2_r	Try it »
Set3	Try it »	Set3_r	Try it »
Spectral	Try it »	Spectral_r	Try it »
Wistia	Try it »	Wistia_r	Try it »
YlGn	Try it »	YlGn_r	Try it »
YlGnBu	Try it »	YlGnBu_r	Try it »
YlOrBr	Try it »	YlOrBr_r	Try it »
YlOrRd	Try it »	YlOrRd_r	Try it »
afmhot	Try it »	afmhot_r	Try it »
autumn	Try it »	autumn_r	Try it »
binary	Try it »	binary_r	Try it »
bone	Try it »	bone_r	Try it »
brg	Try it »	brg_r	Try it »
bwr	Try it »	bwr_r	Try it »
cividis	Try it »	cividis_r	Try it »
cool	Try it »	cool_r	Try it »
coolwarm	Try it »	coolwarm_r	Try it »
copper	Try it »	copper_r	Try it »
cubehelix	Try it »	cubehelix_r	Try it »
flag	Try it »	flag_r	Try it »
gist_earth	Try it »	gist_earth_r	Try it »
gist_gray	Try it »	gist_gray_r	Try it »
gist_heat	Try it »	gist_heat_r	Try it »
gist_ncar	Try it »	gist_ncar_r	Try it »
gist_rainbow	Try it »	gist_rainbow_r	Try it »
gist_stern	Try it »	gist_stern_r	Try it »
gist_yarg	Try it »	gist_yarg_r	Try it »
gnuplot	Try it »	gnuplot_r	Try it »
gnuplot2	Try it »	gnuplot2_r	Try it »
gray	Try it »	gray_r	Try it »
hot	Try it »	hot_r	Try it »
hsv	Try it »	hsv_r	Try it »
inferno	Try it »	inferno_r	Try it »
jet	Try it »	jet_r	Try it »
magma	Try it »	magma_r	Try it »
nipy_spectral	Try it »	nipy_spectral_r	Try it »
ocean	Try it »	ocean_r	Try it »
pink	Try it »	pink_r	Try it »
plasma	Try it »	plasma_r	Try it »
prism	Try it »	prism_r	Try it »
rainbow	Try it »	rainbow_r	Try it »
seismic	Try it »	seismic_r	Try it »
spring	Try it »	spring_r	Try it »
summer	Try it »	summer_r	Try it »
tab10	Try it »	tab10_r	Try it »
tab20	Try it »	tab20_r	Try it »
tab20b	Try it »	tab20b_r	Try it »
tab20c	Try it »	tab20c_r	Try it »
terrain	Try it »	terrain_r	Try it »
twilight	Try it »	twilight_r	Try it »
twilight_shifted	Try it »	twilight_shifted_r	Try it »
viridis	Try it »	viridis_r	Try it »
winter	Try it »	winter_r	Try it »

Hajmi

s argumenti yordamida nuqtalar hajmini o‘zgartirishingiz mumkin.

Ranglar singari, o‘lchamlar uchun massiv x va y o‘qlari uchun massivlar bilan bir xil uzunlikka ega ekanligiga ishonch hosil qiling:

Misol

Belgilar uchun o‘zingizning o‘lchamingizni belgilang:

import matplotlib.pyplot as plt import numpy as np x = np.array([5,7,8,7,2,17,2,9,4,11,12,9,6]) y = np.array([99,86,87,88,111,86,103,87,94,78,77,85,86]) sizes = np.array([20,50,100,200,500,1000,60,90,10,300,600,800,75]) plt.scatter(x, y, s=sizes) plt.show()

Natija:

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Alfa

alphaargumenti yordamida nuqtalarning shaffofligini sozlashingiz mumkin.

Ranglar singari, o‘lchamlar uchun massiv x va y o‘qlari uchun massivlar bilan bir xil uzunlikka ega ekanligiga ishonch hosil qiling:

Misol

Belgilar uchun o‘zingizning o‘lchamingizni belgilang:

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Rang hajmi va alfani birlashtiring

Rang xaritasini turli o‘lchamdagi nuqtalar bilan birlashtira olasiz. Agar nuqta shaffof bo‘lsa, buni eng yaxshi ko‘rish mumkin:

Misol

X nuqtalari, y nuqtalari, ranglari va o‘lchamlari uchun 100 ta qiymatga ega tasodifiy massivlarni yarating:

import matplotlib.pyplot as plt import numpy as np x = np.random.randint(100, size=(100)) y = np.random.randint(100, size=(100)) colors = np.random.randint(100, size=(100)) sizes = 10 * np.random.randint(100, size=(100)) plt.scatter(x, y, c=colors, s=sizes, alpha=0.5, cmap='nipy_spectral') plt.colorbar() plt.show()

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