Kwihlabathi lanamhlanje, ukusebenza ngothotho lwedatha sisakhono esibalulekileyo kumphuhlisi. Omnye wemisebenzi eqhelekileyo kukuguqula isitampu sexesha kwixesha elithile, njengedatha yeveki okanye yenyanga. Lo msebenzi ubalulekile kuhlalutyo olwahlukeneyo, njengokufunda iintsingiselo kunye neepateni kwidatha. Kweli nqaku, siza kuphonononga indlela yokuguqula isitampu sexesha kwixesha kwidatha-seti yedatha usebenzisa ithala leencwadi lePython elinamandla, iPandas. Siza kuphinda singene nzulu kwikhowudi, siphonononge amathala eencwadi kunye nemisebenzi ebandakanyekayo kwinkqubo, kwaye siqonde ukubaluleka kwayo ekusombululeni le ngxaki.
I-Pandas i-open-source-source analysis data kunye nelayibrari yokukhwabanisa, ebonelela ngemisebenzi eguquguqukayo kunye nephezulu yokusebenza kunye nedatha yexesha. Yenza umsebenzi wethu ube lula, uchanekile kwaye usebenze kakuhle.
Isisombululo sokuguqula idatha yesitampu sexesha ukuya kwixesha elithile, elifana neveki okanye ngenyanga, libandakanya ukusebenzisa indlela yokuphinda yesampula yethala leencwadi lePandas. Ukuphinda kuqwalaselwe kwakhona sisixhobo esinamandla esinokusetyenziswa kwidatha yesitampu sexesha okanye kwidatha yothotho lwexesha ukwenza isampula okanye ukuthoba iisampulu zeendawo zedatha. Kule meko, siya kuthoba amanqaku edatha ukwenza amaxesha afunekayo.
Ngoku, makhe sijonge inyathelo ngenyathelo lenkcazo yekhowudi:
1. Thatha ngaphandle amathala eencwadi ayimfuneko:
import pandas as pd import numpy as np
2. Yenza isampulu yedata yedata ngesalathiso sesitampu sexesha:
date_rng = pd.date_range(start='1/1/2020', end='1/10/2020', freq='D')
df = pd.DataFrame(date_rng, columns=['date'])
df['data'] = np.random.randint(0,100,size=(len(date_rng)))
df.set_index('date', inplace=True)
3. Sebenzisa kwakhona idatha yoluhlu lwexesha kwaye uguqule idatha yesitampu sexesha ibe ngamaxesha:
df_period = df.resample('W').sum()
4. Shicilela isakhelo sedatha esisiphumo:
print(df_period)
Uluhlu lokugqibela lwedatha `df_period` luqulethe isimbuku sedatha yoqobo edityaniswe ngeveki.
**Ukuqonda amathala eencwadi kunye neMisebenzi eSetyenzisiweyo**
Pandas Library
I-Pandas yilayibrari yePython esetyenziswa ngokubanzi kubuchule bedatha kunye nohlalutyo. Ibonelela ngezakhiwo zedatha ephezulu njengeSeries kunye neDathaFrame, evumela abaphuhlisi ukuba benze imisebenzi efana nokudibanisa, ukubunjwa ngokutsha, kunye nokucoca ngokukhawuleza nangokufanelekileyo. Kwimeko yethu, i-Pandas inceda ukuphatha idatha yesitampu ngokufanelekileyo kwaye ibonelela ngemisebenzi ebalulekileyo njenge-resample () ukuguqula idatha yesitampu sexesha.
Isample Function
The isampuli () umsebenzi kwiPandas yindlela efanelekileyo yokuguqulwa rhoqo kunye nokuphinda kuqwalaselwe idatha yochungechunge lwexesha. Ibonelela ngeendlela ezininzi zokudityaniswa kwedatha okanye ukuthoba isampulu, kubandakanywa isixa, intsingiselo, i-median, imo, kunye neminye imisebenzi echazwe ngumsebenzisi. Sisebenzisa lo msebenzi ukuguqula idatha yethu yesitampu sexesha kwisithuba seveki ngokuchaza uphinda-phindo lwesampulu rhoqo njenge 'W'. Ungasebenzisa u-'M' ngenyanga, u-'Q' ngekota, njalo njalo.
Ngoku ukuba sihlolisise ukusebenza kweePanda kunye nomsebenzi wokubuyisela kwakhona ukuguqula isitampu sexesha kwidatha yexesha, sinokuphatha ngokulula idatha yexesha ngendlela enentsingiselo. Ngoncedo lwezi zixhobo, abaphuhlisi, abahlalutyi bedatha, kunye neengcali ze-SEO banokuvula iingqiqo ezizodwa kwiidatha zabo, zibancede benze izigqibo ezingcono kunye nokubikezela.
