Kwihlabathi lokuguqulwa kwedatha kunye nohlalutyo, ukuphatha amaxabiso alahlekileyo ngumsebenzi obalulekileyo. Iipandas, ilayibrari yePython esetyenziswa ngokubanzi, ivumela ukuba silawule ngokufanelekileyo idatha engekhoyo. Enye indlela eqhelekileyo yokujongana namaxabiso angekhoyo ibandakanya ukusebenzisa izichazi-magama ukwenza imephu nokubuyisela ezi xabiso. Kweli nqaku, siza kuxubusha indlela yokunyusa amandla ePandas kunye nePython ukusebenzisa izichazi-magama zokutshintsha amaxabiso alahlekileyo kwidathasethi.
isisombululo
Isisombululo sokuqala esiza kuphonononga kukusebenzisa i gcwalisa () sebenza ngokubambisana nezichazi-magama. Le ndlela iza kwenza ukuba sitshintshe amaxabiso angekhoyo ngamaxabiso ahambelanayo asuka kwisichazi-magama esikhankanyiweyo.
Inkcazo yenyathelo ngenyathelo lekhowudi
Ukubonisa le nkqubo, masicinge ukuba sineseti yedatha equlethe ulwazi malunga nezitayile ezahlukeneyo zefashoni, kubandakanya iimpahla, imibala, kunye nembali yomxholo. Kwezinye iimeko, kunokubakho amaxabiso alahlekileyo kule datha.
Okokuqala, ngenisa iilayibrari eziyimfuneko kwaye wenze isampulu yeDathaFrame:
import pandas as pd
data = {
'style': ['Grunge', 'Bohemian', 'Preppy', None, 'Punk', 'Casual'],
'garments': ['Plaid shirt', None, 'Blazer', 'Maxi dress', 'Leather jacket', 'T-shirt'],
'colors': ['Black', 'Faded', 'Light', 'Earthy', None, None]
}
df = pd.DataFrame(data)
Ngoku ekubeni sineDathaFrame ebonisa ingxaki, qaphela ukuba amanye amaxabiso alahlekile (echazwa nguNonye). Ukutshintsha la maxabiso, yenza izichazi-magama eziqulethe iimaphu ezifanelekileyo:
style_dict = {None: 'Unknown'}
garments_dict = {None: 'Other'}
colors_dict = {None: 'Various'}
# Combine dictionaries
replacement_dict = {'style': style_dict, 'garments': garments_dict, 'colors': colors_dict}
Ekugqibeleni, sebenzisa ifayile gcwalisa () umsebenzi ukubuyisela amaxabiso angekhoyo usebenzisa isichazi-magama esidityanisiweyo:
df_filled = df.fillna(replacement_dict)
Ukuqonda ithala leencwadi lePandas
Iipandas lithala leencwadi elisebenza ngeendlela ezininzi ePython elenzelwe ukukhohlisa kunye nohlalutyo lwedatha. Inika izakhiwo zedatha eziguquguqukayo nezinamandla ezifana neSeries kunye neDathaFrame. Ezi zakhiwo ziyimfuneko ekusebenzeni ngokufanelekileyo kunye nedatha ehleliweyo, ye-tabular.
IiPandas zibonelela ngengqokelela etyebileyo yemisebenzi, njenge gcwalisa (), esetyenziselwa ukuphatha idatha engekhoyo. Eminye imisebenzi, efana nokudibanisa idatha, i-pivoting data, kunye nohlalutyo loluhlu lwexesha, lunokwenziwa ngaphandle komthungo kunye neePandas.
Imisebenzi yokuphatha idatha engekhoyo
Ukongeza kwi gcwalisa () Umsebenzi, iiPandas zibonelela ngemisebenzi emininzi kunye neendlela zokujongana nedatha engekhoyo, efana nale:
- dropna (): Susa imiqolo okanye iikholamu ezinedatha engekhoyo.
- isna(): Qinisekisa ukuba yeyiphi i-DataFrame okanye iSeries elements ezingekhoyo okanye ezingekho.
- hayi(): Qinisekisa ukuba yeyiphi i-DataFrame okanye iSeries elements ezingekhoyo okanye ezingekho.
- interpolate(): Gcwalisa amaxabiso angekhoyo usebenzisa utolikeko lomgama.
Ezi ndlela, kunye gcwalisa (), unikeze uluhlu olubanzi lwezixhobo zokuphatha idatha engekhoyo kwiimeko ezahlukeneyo.
Ekugqibeleni, eli nqaku libonise indlela yokusebenzisa yiyalela ukubuyisela amaxabiso angekhoyo kwiPandas DataFrame. Umsebenzi ophambili esiwusebenzisileyo, gcwalisa (), sisixhobo esinamandla kwilayibrari yePandas esivumela ukuba siphathe idatha engekhoyo ngokufanelekileyo. Ngokusebenzisa izichazi-magama, sinokwenza imephu yamaxabiso angekhoyo ukuze sithathe indawo efanelekileyo kwaye siqinisekise ukuba iseti yethu yedatha igqibelele kwaye inentsingiselo. Ngokuqonda okunzulu kwethala leencwadi lePandas kunye nemisebenzi efakiweyo, sinokusebenza kunye neeseti zedatha enkulu ngokufanelekileyo kwaye sifumane ulwazi oluxabisekileyo kwiidatha zethu.
