Emhlabeni wanamuhla, ukusebenza ngedatha yochungechunge lwesikhathi kuyikhono elibalulekile kunjiniyela. Omunye wemisebenzi evamile ukuguqula isitembu sesikhathi sibe enkathini ethile, njengedatha yangeviki noma yenyanga. Lo msebenzi ubalulekile ekuhlaziyeni okuhlukahlukene, njengokufunda amathrendi namaphethini kudatha. Kulesi sihloko, sizohlola ukuthi singasiguqula kanjani isitembu sesikhathi sibe isikhathi kudathasethi yochungechunge lwesikhathi sisebenzisa umtapo wezincwadi wePython onamandla, iPandas. Sizophinde singene sijule kukhodi, sihlole imitapo yolwazi nemisebenzi ehilelekile kule nqubo, futhi siqonde ukubaluleka kwayo ekuxazululeni le nkinga.
I-Pandas iwumthombo ovulekile wokuhlaziya idatha nomtapo wolwazi wokukhohlisa, ohlinzeka ngemisebenzi eguquguqukayo nesebenza kahle kakhulu ukuze isebenze nedatha yochungechunge lwesikhathi. Kwenza umsebenzi wethu ube lula, unembile, futhi usebenze kahle.
Isixazululo sokuguqula idatha yesitembu sesikhathi ibe enkathini ethile, njengeviki ngalinye noma nyanga zonke, sihlanganisa ukusebenzisa indlela yokuphinda isampula yomtapo we-Pandas. Ukwenza isampula kabusha ithuluzi elinamandla elingasetshenziswa kudatha yesitembu sesikhathi noma idatha yochungechunge lwesikhathi ukuze kusale noma kuthathwe isampula amaphuzu edatha. Kulokhu, sizokwehlisa amaphoyinti edatha ukuze sidale izikhathi ezifiselekayo.
Manje, ake sibheke incazelo yesinyathelo nesinyathelo sekhodi:
1. Ngenisa imitapo yolwazi edingekayo:
import pandas as pd import numpy as np
2. Dala isampula yohlaka lwedatha ngenkomba yesitembu sesikhathi:
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. Lingisa kabusha idatha yochungechunge lwesikhathi futhi uguqule idatha yesitembu sesikhathi ibe yizikhathi:
df_period = df.resample('W').sum()
4. Phrinta ifreyimu yedatha ewumphumela:
print(df_period)
Uhlaka lwedatha lokugcina `df_period` luqukethe isamba sedatha yoqobo ehlanganiswe ngeviki.
**Ukuqonda Imitapo yolwazi kanye Nemisebenzi Esetshenziswayo**
I-Pandas Library
I-Pandas iwumtapo wezincwadi wePython osetshenziswa kabanzi wokukhohlisa nokuhlaziya idatha. Ihlinzeka ngezakhiwo zedatha yezinga eliphezulu njenge-Series ne-DataFrame, evumela onjiniyela ukuthi benze imisebenzi efana nokuhlanganisa, ukubunjwa kabusha, nokuhlanza ngokushesha nangempumelelo. Esimweni sethu, i-Pandas isiza ukuphatha idatha yesitembu sesikhathi ngempumelelo futhi inikeza imisebenzi ebalulekile efana ne-resample() ukuguqula idatha yesitembu sesikhathi ibe izikhathi.
Umsebenzi Wesampula
The isampula() umsebenzi kuma-Pandas kuyindlela elula yokuguqula imvamisa nokuphinda kwenziwe isampula yedatha yochungechunge lwesikhathi. Inikeza izinketho eziningi zokuhlanganiswa kwedatha noma ukwehliswa kwesampula, okuhlanganisa isamba, incazelo, imidiyeni, imodi, neminye imisebenzi echazwe umsebenzisi. Sisebenzisa lo msebenzi ukuguqula idatha yethu yesitembu sesikhathi ibe isikhathi seviki ngokucacisa imvamisa yokuphinda isampula njengokuthi 'W'. Ungasebenzisa futhi u-'M' nyanga zonke, u-'Q' njalo ngekota, njalo njalo.
Manje njengoba sesihlole ukusebenza kwe-Pandas nomsebenzi wesampula kabusha wokuguqula isitembu sesikhathi sibe idatha yesikhathi, singakwazi ukuphatha kalula idatha ezwela isikhathi ngendlela ephusile. Ngosizo lwalawa mathuluzi, onjiniyela, abahlaziyi bedatha, nochwepheshe be-SEO bangavula imininingwane ehlukile kudatha yabo, babasize benze izinqumo ezingcono nokuqagela.
