Kuxazululiwe: ama-panda agcwalisa emuva ngemva kokwenziwa kwesampula

Emhlabeni wanamuhla, ukukhohlisa nokuhlaziya idatha kubalulekile ukuze uqonde izenzakalo ezihlukahlukene nokwenza izinqumo ezinolwazi. Omunye wemisebenzi evamile ekuhlaziyweni kwedatha ukuhlola kabusha idatha yochungechunge lwesikhathi, okubandakanya ukushintsha imvamisa yedatha, ngokunyusa (ukwandisa imvamisa) noma ngokwehlisa (ukwehlisa imvamisa). Kulesi sihloko, sizoxoxa ngenqubo yokugcwalisa emuva ngenkathi siphakamisa idatha yochungechunge lwesikhathi sisebenzisa umtapo wezincwadi wePython onamandla, iPandas.

Gcwalisa Emuva Ngedatha Yochungechunge Lwesikhathi

Uma senza isibonelo sedatha yochungechunge lwesikhathi, sinyusa imvamisa yamaphoyinti edatha, ngokuvamile okuholela kumanani ashodayo wamaphoyinti edatha adalwe kabusha. Ukuze sigcwalise la manani angekho, singasebenzisa izindlela ezihlukahlukene. Enye indlela enjalo ibizwa ngokuthi ukugcwaliswa emuva, obeye aziwe njengo ukubuyisela emuva. Ukugcwalisa emuva kuyinqubo yokugcwalisa amanani angekho ngevelu elandelayo etholakalayo ochungechungeni lwesikhathi.

I-Pandas Library

AmaPython Umtapo wezincwadi wePandas iyithuluzi elibalulekile lokukhohlisa idatha, elinikeza ububanzi obubanzi bemisebenzi yokuphatha izakhiwo zedatha njenge-DataFrames nedatha yochungechunge lwesikhathi. I-Pandas inezici ezakhelwe ngaphakathi ezenza kube lula ukusebenza ngedatha yochungechunge lwesikhathi, njengokusampula kabusha nokugcwalisa amanani angekho, okusenza sikwazi ukwenza ukugcwalisa ngokuhlehlela emuva ngemva kokwenza isampula.

Isixazululo: Gcwalisa Emuva ngamaPanda

Ukubonisa inqubo yokusebenzisa ukugcwaliswa okubuyela emuva ngemva kokusampula idatha yochungechunge lwesikhathi kusetshenziswa ama-Panda, ake sicabangele isibonelo esilula. Sizoqala ngokungenisa amalabhulali adingekayo futhi sidale isampula yedathasethi yochungechunge lwesikhathi.

import pandas as pd
import numpy as np

# Create a sample time series dataset
date_rng = pd.date_range(start='2022-01-01', end='2022-01-10', freq='D')
data = np.random.randint(0, 100, size=(len(date_rng), 1))

df = pd.DataFrame(date_rng, columns=['date'])
df['value'] = data

Manje njengoba sesinedatha yethu yesampula, sizoqhubeka nokusampula futhi sisebenzise indlela yokugcwalisa emuva. Kulesi sibonelo, sizokwenyusa imvamisa yansuku zonke kuye kweyehora:

# Upsample the data to hourly frequency
df.set_index('date', inplace=True)
hourly_df = df.resample('H').asfreq()

# Apply the backward fill method to fill missing values
hourly_df.fillna(method='bfill', inplace=True)

Ekhodini engenhla, siqale sisethe ikholomu 'yedethi' njengenkomba bese senza isampula kabusha idatha ibe imvamisa yehora sisebenzisa isampula() umsebenzi. I-DataFrame ewumphumela inamanani ashodayo ngenxa yokwanda kobuningi. Sabe sesisebenzisa i- gcwalisa() indlela enepharamitha ethi 'bfill' ukwenza ukugcwalisa emuva kumanani angekho.

Isinyathelo ngesinyathelo Incazelo

Ake sihlukanise ikhodi ukuze siyiqonde kangcono:

1. Siqale sangenisa imitapo yolwazi yakwaPanda neNumPy:

   import pandas as pd
   import numpy as np
   

2. Sakhe isampula yedatha yochungechunge lwesikhathi sisebenzisa i date_range() umsebenzi kusuka ku-Panda ukukhiqiza izinsuku zansuku zonke namanani ezinombolo angahleliwe:

   date_rng = pd.date_range(start='2022-01-01', end='2022-01-10', freq='D')
   data = np.random.randint(0, 100, size=(len(date_rng), 1))
   df = pd.DataFrame(date_rng, columns=['date'])
   df['value'] = data
   

3. Okulandelayo, simisa ikholomu 'yosuku' njengenkomba futhi saphinda sasampula idatha ibe imvamisa yehora nge isampula() futhi i-asfreq() imisebenzi:

   df.set_index('date', inplace=True)
   hourly_df = df.resample('H').asfreq()
   

4. Ekugcineni, sigcwalise amanani angekho ku-DataFrame esampuliwe sisebenzisa i- gcwalisa() indlela enepharamitha ye-'bfill' yokugcwalisa emuva:

   hourly_df.fillna(method='bfill', inplace=True)
   

Isiphetho

Kulesi sihloko, sihlole inqubo ye ukugcwaliswa emuva ngemva kokulinganisa idatha yochungechunge lwesikhathi usebenzisa umtapo wezincwadi wePandas onamandla ePython. Ngokuqonda nokusebenzisa lawa maqhinga, singakwazi ukukhohlisa futhi sihlaziye idatha yochungechunge lwesikhathi, sithole imininingwane ebalulekile futhi senze izinqumo ezinolwazi.