Ukutenxa okukhulu kwiPandas sisihloko esinomdla xa kufikwa kuhlalutyo lwedatha kunye nokukhohlisa usebenzisa iPandas yelayibrari eyaziwayo yePython. Enye yezinto eziphambili zokuhlalutya idatha kukuchonga ukuhluka ngaphakathi kwedatha, enokwenziwa ngokubala ukuphambuka okukhulu. Kweli nqaku, siza kufunda indlela yokubala ukutenxa okukhulu kwiPandas, siphonononge iindlela ezahlukeneyo kwaye sijonge nzulu kwezinye iilayibrari ezifanelekileyo kunye nemisebenzi enokusetyenziswa ukusombulula le ngxaki.
Ubuninzi bokutenxa kubhekisa kuwona mahluko uphezulu phakathi kwexabiso kwiseti yedatha kunye nentsingiselo okanye i-median yaloo seti yedatha. Kwizibalo, ukutenxa kunceda ukuqonda ukusasazwa kunye nokwahluka kwamanqaku edatha ngaphakathi kweseti yedatha. Ingumbono obalulekileyo odla ngokusetyenziswa kuhlalutyo lwemali, ukusetyenzwa komqondiso, kunye neminye imimandla yobungakanani.
Isisombululo kwiNgxaki
Ukubala ukutenxa okukhulu kwiPandas, sinokuqala ngokungenisa ngaphandle iilayibrari eziyimfuneko kunye nokudala isampuli yeDathaFrame. Emva koko, siya kubala intsingiselo okanye i-median yedatha kwaye sifumane umgama ophezulu phakathi kwendawo nganye yedatha kunye ne-meaning / median. Okokugqibela, sizakusebenzisa max() umsebenzi ukufumana elona xabiso liphezulu phakathi kwezi zinxaxhi zipheleleyo.
Nantsi ikhowudi yomzekelo ebonisa indlela yokubala ukutenxa okukhulu kwiPandas DataFrame:
import pandas as pd
# Sample data
data = {'Value': [5, 7, 11, 18, 23, 25, 29, 35, 40, 50]}
df = pd.DataFrame(data)
# Compute mean and median
mean = df['Value'].mean()
median = df['Value'].median()
# Calculate absolute deviations from mean and median
df['Mean Deviation'] = (df['Value'] - mean).abs()
df['Median Deviation'] = (df['Value'] - median).abs()
# Find max deviation
max_mean_deviation = df['Mean Deviation'].max()
max_median_deviation = df['Median Deviation'].max()
print("Max Deviation from Mean: ", max_mean_deviation)
print("Max Deviation from Median: ", max_median_deviation)
Inkcazo ngeNyathelo ngeNyathelo
Ngoku masiye kwikhowudi inyathelo ngenyathelo ukuqonda inkqubo yokubala ukutenxa okukhulu kwiPandas DataFrame:
1. Okokuqala, singenisa ilayibrari yepandas kwaye senze isampuli yeDathaFrame kunye nekholamu enye ebizwa ngokuba 'Ixabiso'.
2. Emva koko sibala i-mendi kunye ne-median yedatha usebenzisa i-mean () kunye ne-median () imisebenzi enikezwe yiPandas.
3. Emva koko, sibala ukutenxa ngokupheleleyo kwindawo nganye yedatha ngokukhupha i-meaning kunye ne-median kwiindawo ezichaphazelekayo zedatha, kwaye sithathe ixabiso elipheleleyo lomahluko obangelwayo.
4. Okokugqibela, sisebenzisa max() umsebenzi ukufumana elona xabiso liphezulu phakathi kwezitenxo ezipheleleyo.
5. Isiphumo siya kubonisa ukutenxa okukhulu ukusuka kumbindi wentsingiselo kunye ne-median yedatha.
Amathala eencwadi aNxulumeneyo kunye neMisebenzi
- Iipandas: Eli lilayibrari ephambili esetyenziswa kweli nqaku, kwaye yamkelwa ngokubanzi ngesakhono salo sokukhohlisa idatha. Imisebenzi edla ngokusetyenziswa njenge mean(), median(), max(), min(), kunye abs() yinxalenye yethala leencwadi lePandas.
- I-NumPy: Eli lelinye ithala leencwadi lekhompyuter elidumileyo ePython, elibonelela ngenkxaso ebanzi yokusebenza ngoluhlu kunye nokusebenza kwamanani. Kwezinye iimeko, umntu unokusebenzisa imisebenzi ye-NumPy ukuphumeza imisebenzi efana nePandas.
Ukuququmbela
Ukuchonga ukuphambuka okukhulu kwiPandas kuyinkalo ebalulekileyo yohlalutyo lwedatha, okukuvumela ukuba ulinganise ukusabalalisa ngaphakathi kwedatha, kwaye eli nqaku liye lachaza indlela echanekileyo yokwenza lo msebenzi. Ngokusetyenziswa kwePandas imisebenzi enje nge mean(), median(), abs(), kunye max(), kuba lula ukubala ngokufanelekileyo ukutenxa kukhulu kuyo nayiphi na idataset enikiweyo. Ngaphaya koko, imisebenzi efanayo kunye nokusebenza kungaphunyezwa kusetyenziswa amathala eencwadi afana neNumPy, encedisana kwaye yandise umda weendlela zokuguqula idatha ezifumanekayo kumphuhlisi.
