Ilayibrari ye-pandas yePython lithala leencwadi elinamandla neliguquguqukayo lokukhohlisa kunye nohlalutyo lwedatha, ngakumbi xa usebenza ngedatha yetheyibhile ngohlobo lweefreyimu zedatha. Umsebenzi omnye oqhelekileyo xa usebenza ngedataframes kukulungisa kwakhona ulandelelwano lwekholomu ukuze lulingane neemfuno ezithile. Kweli nqaku, siya kugxininisa kwindlela yokutshintsha ikholamu yokugqibela kwindawo yokuqala kwi-dataframe ye-pandas. Oku kunokuba luncedo ngakumbi xa ufuna ukuzisa ingqalelo kwimihlathi ethile, ngakumbi xa isethi yedatha inenani elikhulu leekholamu.
Ukusombulula lo mba, siya kusebenzisa umsebenzi osisiseko onikwe yi-pandas, njenge-database indexing kunye nokuhlelwa kwakhona kwekholamu. Injongo ephambili kukukhupha ikholamu yokugqibela kwi-dataframe kwaye uyifake kwindawo yokuqala ngelixa ugcina umyalelo wezinye iikholomu.
Okokuqala, masingenise ilayibrari ye-pandas kwaye senze i-dataframe elula kunye neekholamu ezine:
import pandas as pd
data = {'A': [1, 2, 3],
'B': [4, 5, 6],
'C': [7, 8, 9],
'D': [10, 11, 12]}
df = pd.DataFrame(data)
print(df)
Oku kuya kubonisa olu luhlu lwedatha lulandelayo:
A B C D 0 1 4 7 10 1 2 5 8 11 2 3 6 9 12
Ngoku, masishukumise umhlathi wokugqibela (uluhlu 'D') lube ngumhlathi wokuqala, kwaye sitshintshe ezinye iikholamu ngokufanelekileyo. Isisombululo siquka umgca omnye wekhowudi:
df = df[df.columns[-1:].tolist() + df.columns[:-1].tolist()] print(df)
Oku kuya kukhupha isakhelo sedatha esilungisiweyo:
D A B C 0 10 1 4 7 1 11 2 5 8 2 12 3 6 9
I-Pandas DataFrame Column Manipulation ecacisiweyo
Nantsi inyathelo ngenyathelo inkcazo yekhowudi esusa ikholamu yokugqibela kwindawo yokuqala:
1. Sikhupha ikholamu yokugqibela sisebenzisa isalathisi: `df.columns[-1:]`. Oku kufumana kwakhona igama lomhlathi wokugqibela, kwaye siliguqulela kuluhlu sisebenzisa indlela `yoluhlu ()`.
2. Sikhupha zonke iikholamu ngaphandle kweyokugqibela: `df.columns[:-1]`. Oku kuthatha kwakhona amagama ayo yonke imihlathi ngaphandle kweyokugqibela, kwaye siyiguqulela kuluhlu sisebenzisa indlela `yoluhlu ()`.
3. Sidibanisa uluhlu: `df.columns[-1:].tolist() + df.columns[:-1].tolist()`. Oku kudala uluhlu olutsha kunye negama lekholamu yokugqibela ekuqaleni, lilandelwa ngamanye amagama eekholamu ngendlela yawo yoqobo.
4. Sisebenzisa umyalelo omtsha wekholomu kwi-dataframe: `df[df.columns[-1:].tolist() + df.columns[:-1].tolist()]`. Oku kudala i-dataframe entsha kunye nomyalelo wekholamu efunwayo.
Ukuphucula izakhono zakho ngeePandas
Ithala leencwadi le-pandas lineempawu ezininzi zokuphatha, ukulawula kunye nokuhlalutya idataframes. Kulo mzekelo, sibonise indlela yokutshintsha ikholamu yokugqibela kwindawo yokuqala kwi-dataframe. Obu buchule buluncedo ekuhlengahlengiseni nasekugxininiseni kwiikholamu ezithile ngaphakathi kwedathasethi.
Ukusebenza nge-dataframes yinkalo enye kuphela yeepanda, njengoko ithala leencwadi likwabonisa izixhobo zokuphatha uthotho lwexesha kunye nezinye izakhiwo zedatha ezinzima. Ukuze ube nobuchule kwilayibrari ye-pandas yePython, kubalulekile ukuqonda imisebenzi eyahlukeneyo efana isalathiso, ukudibanisa, yaye ukucwangcisa ngokutsha ikholamu - zonke ezi zinto zibalulekile kulawulo lwedatha olusebenzayo.
Ukongeza, iipandas zixhasa imisebenzi emininzi efana nokucoca, ukudibanisa, kunye nokucoca, nto leyo eyenza ukuba ibe sisixhobo esiyimfuneko kuhlahlelo lwedatha. Kucetyiswa kakhulu ukuba uphonononge izihloko eziphambili kunye neendlela zokwandisa amandla e-pandas kunye nokuphucula imizamo yakho yokukhohlisa idatha.
