I-Pandas iwumtapo wezincwadi wePython onamandla futhi osetshenziswa kabanzi wokukhohlisa nokuhlaziya idatha. Umsebenzi owodwa ovamile lapho usebenza namasethi edatha uyisidingo sokuthola amanani ahlukile kukholomu ngayinye. Lokhu kungaba usizo ekuqondeni ukuhlukahluka nokusatshalaliswa kwamanani kudatha yakho, kanye nokuhlonza okungase kube khona amaphutha namaphutha. Kulesi sihloko, sizohlola ukuthi singawufeza kanjani lo msebenzi sisebenzisa amaPanda futhi sinikeze incazelo enemininingwane, yesinyathelo nesinyathelo yekhodi ehilelekile. Sizophinde sixoxe ngamalabhulali ahlobene nemisebenzi engase ibe usizo lapho isebenza ngamavelu ahlukile neminye imisebenzi yokuhlaziya idatha.
Ukuze uxazulule inkinga yokuthola amanani ahlukile kukholomu ngayinye kusetshenziswa ama-Panda, sizodinga kuqala ukungenisa umtapo wolwazi futhi sifunde kudathasethi yethu. Uma sesineDathaFrame yethu, singabese sisebenzisa imisebenzi ethi `nunique()` kanye `neyingqayizivele()` ukuze sithole futhi sibonise amanani ayingqayizivele ekholomu ngayinye.
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)
Kumazwibela ekhodi ngenhla, siqala ngokungenisa umtapo wezincwadi we-Pandas futhi sifunde kudathasethi yethu sisebenzisa umsebenzi othi `pd.read_csv()`. Okulandelayo, siphindaphinda ikholomu ngayinye ku-DataFrame sisebenzisa i-loop. Ngaphakathi kweluphu, sisebenzisa umsebenzi othi `nunique()` ukuze sithole inani lamanani ahlukile kukholamu yamanje, nomsebenzi `oyingqayizivele()` ukuze sithole amanani afanayo ahlukile ngokwawo. Ekugcineni, siphrinta imiphumela sisebenzisa amayunithi ezinhlamvu afomethiwe.
I-Pandas nunique() kanye nemisebenzi eyingqayizivele()
I-pandas nunique() kuwumsebenzi owusizo obuyisela inani lamanani ahlukile kukholomu yochungechunge olunikeziwe noma i-DataFrame. Lokhu kungaba usizo lapho uzama ukuqonda ubunkimbinkimbi nokwehlukahlukana kwedathasethi. Icabangela noma yimaphi amanani angekho (njenge-“NaN”) futhi awafaki ngokuzenzakalela. Uma ufuna ukufaka amanani angekho esibalweni, ungasetha ipharamitha ethi `dropna` ibe `Amanga`, njengokuthi: `i-nunique(dropna=False)`.
I-pandas eyingqayizivele() kungomunye umsebenzi obalulekile obuyisela amanani afanayo ahlukile kukholomu yochungechunge olucacisiwe noma i-DataFrame. Ngokungafani nokuthi `i-nunique()`, lo msebenzi empeleni ubuyisela amanani ayingqayizivele ngokwawo, okukuvumela ukuthi uqhubeke uhlaziye, uwenze, noma uwabonise njengoba kudingeka.
Ndawonye, le misebenzi ihlinzeka ngendlela enamandla nephumelelayo yokuthola nokusebenza ngamavelu ahlukile kudathasethi yakho.
Imitapo yolwazi ehlobene yokuhlaziywa kwedatha
numpy iwumtapo wezincwadi wePython odumile wekhompuyutha yezinombolo ovame ukusetshenziswa ngokuhlangana namaPanda. Ihlinzeka ngemisebenzi eminingi yezibalo namathuluzi okusebenza ngama-n-dimensional arrays kanye namatrices. Lapho iphatha amasethi edatha amakhulu kanye nezibalo eziyinkimbinkimbi, i-Numpy ingaba usizo ngokukhethekile ekuthuthukisweni kwayo kokusebenza kanye nezakhiwo zedatha ezithuthukisiwe.
Scikit-funda ingumtapo wolwazi onamandla wokufunda ngomshini ePython. Ihlinzeka ngama-algorithms ahlukahlukene okuhlelwa, ukuhlehla, ukuhlanganisa, nokunciphisa ubukhulu, kanye namathuluzi okucubungula ngaphambilini idatha, ukukhetha amamodeli, nokuhlola. Uma usebenza ngamavelu ahlukile nezinye izici zedathasethi yakho ukuze wakhe amamodeli aqagelayo noma wenze eminye imisebenzi yokufunda ngomshini, i-Scikit-learn iyilabhulali ozofuna ukuyihlola ngokuqhubekayo.
Sengiphetha, ukuthola amanani ayingqayizivele kukholomu ngayinye yedathasethi kuyisinyathelo esibalulekile ekuhlaziyeni idatha eminingi nasekucubunguleni kusengaphambili ukuhamba komsebenzi. I-Pandas ihlinzeka ngemisebenzi `eyinunique()` ephumelelayo nesebenziseka kalula `kanye neyingqayizivele()` ukuze isize ngalo msebenzi, futhi ukuqonda ukusetshenziswa kwayo kungathuthukisa kakhulu isivinini nokusebenza kwamaphrojekthi akho okuhlaziya idatha. Ukwengeza, ukwandisa ulwazi lwakho lwemitapo yolwazi ehlobene, efana ne-Numpy kanye ne-Scikit-learn, kungathuthukisa amakhono akho ekuguquleni idatha nasekuhlaziyeni, kukubeka empumelelweni emkhakheni okhula njalo wesayensi yedatha.
