Isonjululwe: iipandas ixabiso elikhethekileyo ikholamu nganye

I-Pandas lithala leencwadi lePython elinamandla kwaye lisetyenziswa ngokubanzi ukukhohlisa kunye nohlalutyo lwedatha. Umsebenzi omnye oqhelekileyo xa usebenza ngeeseti zedatha yimfuneko yokufumana amaxabiso awodwa kwikholamu nganye. Oku kunokuba luncedo ekuqondeni iyantlukwano kunye nokuhanjiswa kwamaxabiso kwidatha yakho, kunye nokuchonga izinto ezinokubakho kunye neempazamo. Kule nqaku, siza kuphonononga indlela yokuphumeza lo msebenzi usebenzisa iPandas kwaye unike inkcazo ecacileyo, inyathelo ngenyathelo lekhowudi echaphazelekayo. Siza kuxoxa kwakhona ngamathala eencwadi anxulumeneyo kunye nemisebenzi enokuba luncedo xa usebenza ngexabiso elilodwa kunye neminye imisebenzi yohlalutyo lwedatha.

Ukusombulula ingxaki yokufumana ixabiso elikhethekileyo kwikholamu nganye usebenzisa iPandas, kuya kufuneka kuqala singenise ilayibrari kwaye sifunde kwidathasethi yethu. Sakuba sineDataFrame yethu, sinokusebenzisa `inunique()` kunye `neyahlukileyo()` imisebenzi ukufumana nokubonisa amaxabiso awodwa kuluhlu ngalunye.

import pandas as pd

# Read in the dataset
data = pd.read_csv('your_data_file.csv')

# Find and display the unique values for each column
for column in data.columns:
    unique_count = data[column].nunique()
    unique_values = data[column].unique()
    print(f"Column '{column}' has {unique_count} unique values:")
    print(unique_values)

Kusiqwengana sekhowudi engentla, siqala ngokuthatha ngaphandle ilayibrari yePandas kwaye sifunde kwidatha yethu sisebenzisa `pd.read_csv()` umsebenzi. Okulandelayo, siphindaphinda kwikholamu nganye kwiDathaFrame usebenzisa i-loop. Ngaphakathi kwiluphu, sisebenzisa `inunique ()` umsebenzi ukufumana inani lamaxabiso awodwa kuluhlu lwangoku, kunye nomsebenzi `owodwa ()` ukubuyisela uluhlu lwamaxabiso awodwa ngokwawo. Ekugqibeleni, siprinta iziphumo ngokusebenzisa imitya efomathiweyo.

I-Pandas nunique () kunye neyodwa () Imisebenzi

Pandas nunique() ngumsebenzi oluncedo obuyisela inani lamaxabiso awodwa kuthotho olunikiweyo okanye umhlathi weDataFrame. Oku kunokuba luncedo xa uzama ukuqonda ukuntsokotha ngokubanzi kunye nokwahlukana kwedatha. Ithathela ingqalelo nawaphi na amaxabiso angekhoyo (njenge "NaN") kwaye awabandakanyi ngokungagqibekanga. Ukuba ufuna ukubandakanya amaxabiso angekhoyo ekubaleni, ungacwangcisa i `dropna` iparameter ku `False`, ngolo hlobo: `nunique(dropna=False)`.

IiPanda ezikhethekileyo () ngomnye umsebenzi oxabisekileyo obuyisela uluhlu lwamaxabiso awodwa kuthotho oluchaziweyo okanye ikholamu yeDathaFrame. Ngokungafaniyo ne `nunique()`, lo msebenzi ngenene ubuyisela amaxabiso awodwa ngokwawo, ikuvumela ukuba uqhubekise uhlalutyo, uqhathe, okanye uwabonise njengoko kufuneka.

Ngokudibeneyo, le misebenzi ibonelela ngendlela enamandla nesebenzayo yokufumana kunye nokusebenza ngamaxabiso awodwa kwidatha yakho.

Amathala eencwadi anxulumeneyo kuHlahlelo lweDatha

numpy lilayibrari yePython edumileyo yekhompyuter yamanani ehlala isetyenziswa kunye neePandas. Inika uluhlu olubanzi lwemisebenzi yemathematika kunye nezixhobo zokusebenza kunye ne-n-dimensional arrays kunye nematrices. Xa uphethe iiseti zedatha ezinkulu kunye nokubala okuntsokothileyo, iNumpy inokuba luncedo ngakumbi kuphuculo lokusebenza kunye nolwakhiwo lwedatha olwandisiweyo.

Scikit-funda lilayibrari enamandla yokufunda koomatshini kwiPython. Ibonelela ngeendidi ze-algorithms zokuhlela, ukuhlehla, ukuhlanganisana, kunye nokunciphisa ubukhulu, kunye nezixhobo zokulungiswa kwedatha, ukukhetha imodeli, kunye nokuvavanya. Ukuba usebenza ngamaxabiso awodwa kunye nezinye iimpawu zeseti yedatha yakho ukwakha imifuziselo eqikelelweyo okanye wenze eminye imisebenzi yokufunda koomatshini, iScikit-learn lithala leencwadi oya kufuna ukuliphonononga ngakumbi.

Ukuqukumbela, ukufumana amaxabiso akhethekileyo kwikholamu nganye yedatha linyathelo elibalulekileyo kuhlalutyo oluninzi lwedatha kunye nokuhamba komsebenzi kwangaphambili. I-Pandas ibonelela ngendlela esebenzayo nekulula ukuyisebenzisa `i-nunique()` kunye `neyodwa()` imisebenzi ukunceda kulo msebenzi, kunye nokuqonda ukusetyenziswa kwayo kunokuphucula kakhulu isantya kunye nokusebenza kweeprojekthi zakho zokuhlalutya idatha. Ukongeza, ukwandisa ulwazi lwakho lwamathala eencwadi anxulumeneyo, anje ngeNumpy kunye neScikit-learn, kunokuphucula ngakumbi amandla akho ekwenziweni kwedatha kunye nohlalutyo, kukubeka kwimpumelelo kwicandelo elihlala likhula lesayensi yedatha.