intshayelelo
I-Python lulwimi lwenkqubo oluguquguqukayo nolusetyenziswa ngokubanzi kwiinkalo ezahlukeneyo, kubandakanya uhlalutyo lwedatha, ubukrelekrele bokwenziwa, kunye nophuhliso lwewebhu. Enye yeelayibrari ezibalulekileyo zokuphatha idatha enkulu kwiPython yi INumPy. I-NumPy ibonelela ngento enamandla ye-N-dimensional array, eyenza sikwazi ukwenza imisebenzi yezibalo entsonkothileyo ngokulula. Enye yemisebenzi ebalulekileyo kuhlalutyo lwedatha yi umsebenzi wokwahlula, esetyenziselwa ukwahlula idatha ibe ngamacandelo amancinci ukuze kuhlalutywe ngakumbi. Kweli nqaku, siza kuntywila kwi-syntax kunye nokusetyenziswa komsebenzi we-NumPy wokwahlula ngokubonelela ngesisombululo esisebenzayo, inkcazo ngenyathelo, kunye nokuxoxa ngamathala eencwadi kunye nemisebenzi ehambelanayo.
Isisombululo kwingxaki:
Masithi sineseti yedatha eveliswe kumboniso wefashoni kwaye sifuna ukuhlalutya izitayile ezahlukeneyo, iintsingiselo, kunye nokudityaniswa kombala. Injongo yethu kukwahlula le datha ibe ngamaqhekeza amancinci ukuze kuhlalutywe ngakumbi. Ukufezekisa oku, siya kusebenzisa i Umsebenzi wokwahlula iNumPy.
import numpy as np
# Sample data (styles, trends, and colors)
data = np.array([["Bohemian", "Oversized", "Earthy"],
["Minimalist", "Tailored", "Monochrome"],
["Classic", "Simple", "Neutrals"],
["Romantic", "Flowy", "Pastels"]])
# Split the data into 2 equal parts using NumPy split function
split_data = np.split(data, 2)
Inkcazo ngenyathelo ngenyathelo lekhowudi:
1. Siqala nge ukungenisa ngaphandle ithala leencwadi leNumPy, esinika imisebenzi efunekayo yokuphatha idatha enkulu.
2. Emva koko senza a iseti yedatha yesampula ngezitayile ezahlukeneyo zefashoni, iintsingiselo, kunye noyilo lwemibala. Olu luhlu lwedatha luluhlu lwe-2D NumPy.
3. Ekugqibeleni, usebenzisa i Umsebenzi wokwahlula iNumPy, sahlula isethi yedatha ibe ngamacandelo amabini alinganayo. I-'split_data' eguquguqukayo ngoku iqulethe iindidi ezimbini ezincinci, nganye inesiqingatha sedatha yoqobo.
Ukuqonda iNumPy kunye nomsebenzi wayo wokwahlulahlula
I-NumPy, emfutshane ye-Numeric Python, ilayibrari ebalulekileyo yokwenza imisebenzi yamanani kwiPython. Yaziwa ngokubanzi ngenxa yayo into esebenzayo ye-N-dimensional uluhlu, esebenza njengesixhobo esinamandla sekhompyutheni yesayensi kunye nohlalutyo lwedatha.
The Ukwahlula kwe-NumPy umsebenzi usetyenziswa ukwahlula uluhlu lwegalelo kwiarrays ezincinci ezininzi ecaleni kwe axis ekhankanyiweyo. Lo msebenzi unokuba luncedo ekwaphuleni iiseti zedatha ezinkulu zibe zincinci, iindawo ezilawulekayo, ngaloo ndlela kube lula ukwenza uhlalutyo oluthile kumacandelo ahlukeneyo edatha.
Eminye imisebenzi yeNumPy yokuguqula idatha
Ngaphandle komsebenzi wokwahlulahlula, iNumPy ikwabonelela neminye imisebenzi emininzi yokukhohlisa idatha, efana nale:
- lungisa kwakhona: Lo msebenzi usetyenziselwa ukutshintsha ubume boluhlu olunikiweyo ngaphandle kokuguqula idatha engaphantsi. Ingasetyenziswa ukuguqula uluhlu lwe-dimensional enye ibe luluhlu lwe-dimensional-dimensional okanye ngokuchaseneyo.
- dibanisa: Lo msebenzi usetyenziselwa ukudibanisa ezimbini okanye ngaphezulu uluhlu lwemigca ekhankanyiweyo. Kunokuba luncedo xa udibanisa idatha evela kwimithombo eyahlukeneyo.
- hstack: Lo msebenzi usetyenziselwa ukupakisha uluhlu oluthe tye (uluhlu-bulumko) ecaleni kweasi enye. Kuluncedo ukudibanisa iikholamu kuluhlu olusele lukhona okanye ukwenza uluhlu olutsha ngokudibanisa uluhlu lwezixhobo ezininzi ngapha nangapha.
- vstack: Ngokufanayo ne-hstack, lo msebenzi usetyenziselwa ukupakisha uluhlu oluthe nkqo (umqolo-olumkileyo) ecaleni kweasi enye. Kuluncedo ekuhlomeleni iirowu kuluhlu olusele lukhona okanye ukwenza uluhlu olutsha ngokudibanisa iireyi ezininzi ngaphezulu kwenye.
Ukuqukumbela, i Umsebenzi wokwahlula iNumPy sisixhobo esibalulekileyo sokuphatha idatha enkulu kwiPython. Ngokwahlula isethi yedatha ibe ngamaqhekeza amancinci, sinokuhlalutya ngokufanelekileyo iiseti ezithile zedatha kwaye sikhuphe ulwazi oluxabisekileyo. Ngaphaya koko, ukuqonda imisebenzi enxulumeneyo kunye namathala eencwadi kwi-NumPy kuya kunceda ngakumbi ukuphucula amandla ethu okulawula idatha kwiPython.
