Munyika yekushandiswa kwedata uye kuongorora, kubata hunhu husipo ibasa rakakosha. pandas, raibhurari yePython inoshandiswa zvakanyanya, inotibvumira kubata nemazvo data yakarasika. Imwe nzira yakajairika yekubata nehunhu husipo inosanganisira kushandisa maduramazwi kumepu nekutsiva izvi zvakakosha. Muchinyorwa chino, tichakurukura maitiro ekuwedzera simba rePandas nePython kushandisa maduramazwi ekutsiva nhanho dzakashaikwa mudhata.
mhinduro
Mhinduro yekutanga yatichaongorora ndeye kushandisa iyo kuzadza () kushanda pamwe chete nemaduramazwi. Maitiro aya anozotigonesa kutsiva nhanho dzinoshaikwa netsika dzinoenderana kubva muduramazwi rataurwa.
Nhanho-nhanho tsananguro yekodhi
Kuenzanisira maitiro aya, ngatifungei tine dhatabheti rine ruzivo pamusoro pezvitaera zvakasiyana-siyana zvemafashoni, kusanganisira zvipfeko, mavara, uye nhoroondo. Mune zvimwe zviitiko, panogona kunge pasina kukosha mune ino dataset.
Chekutanga, pinza maraibhurari anodiwa uye gadzira sampuli DataFrame:
import pandas as pd
data = {
'style': ['Grunge', 'Bohemian', 'Preppy', None, 'Punk', 'Casual'],
'garments': ['Plaid shirt', None, 'Blazer', 'Maxi dress', 'Leather jacket', 'T-shirt'],
'colors': ['Black', 'Faded', 'Light', 'Earthy', None, None]
}
df = pd.DataFrame(data)
Zvino zvatava neDataFrame inoratidza dambudziko, cherechedza kuti mamwe maitiro haasipo (anoratidzwa naNone). Kutsiva izvi zvakakosha, gadzira maduramazwi ane mepu yakakodzera:
style_dict = {None: 'Unknown'}
garments_dict = {None: 'Other'}
colors_dict = {None: 'Various'}
# Combine dictionaries
replacement_dict = {'style': style_dict, 'garments': garments_dict, 'colors': colors_dict}
Pakupedzisira, shandisa iyo kuzadza () basa kutsiva hunhu husipo uchishandisa duramazwi rakasanganiswa:
df_filled = df.fillna(replacement_dict)
Kunzwisisa Pandas raibhurari
pandas iraibhurari inoshandiswa zvakasiyana-siyana muPython iyo yakagadzirirwa kushandura data uye kuongorora. Inopa inoshanduka uye ine simba data zvimiro seSeries uye DataFrame. Aya maumbirwo akakosha pakushanda nemazvo neakarongwa, tabular data.
Pandas inopa akapfuma muunganidzwa wemabasa, senge kuzadza (), inoshandiswa kubata data isipo. Mamwe mashandiro, akadai sekubatanidza data, pivoting data, uye nguva-yakatevedzana ongororo, inogona kuitwa isina musono nePandas.
Mabasa ekubata data asipo
Kuwedzera kuzadza () basa, Pandas inopa akati wandei mamwe mabasa uye nzira dzekubata neinoshaikwa data, senge:
- kudonha (): Bvisa mitsara kana makoramu asina data.
- isna(): Sarudza kuti ndeapi DataFrame kana Series zvinhu zvisipo kana zvisina.
- kwete (): Sarudza kuti ndeapi DataFrame kana Series zvinhu zvisiri kushaikwa kana kuti zvisina.
- interpolate(): Zadza hunhu husipo uchishandisa mutsara kududzira.
Nzira idzi, pamwe chete kuzadza (), ipai yakazara suite yezvishandiso zvekubata data rakashaikwa mumamiriro akasiyana-siyana.
Mukupedzisa, chinyorwa ichi chakaratidza nzira yekushandisa raira kutsiva hunhu husipo muPandas DataFrame. Basa rinokosha ratakashandisa, kuzadza (), chishandiso chine simba muraibhurari yePandas inotitendera kubata data rakarasika nemazvo. Nekushandisa maduramazwi, tinogona kumepu kushayikwa kwehunhu kune kwakakodzera kutsiva uye kuona kuti dhatabheti redu rakazara uye rine zvarinoreva. Kuburikidza nekunzwisisa kwakadzama kweraibhurari yePandas uye nemabasa ayo akasanganisirwa, tinogona kushanda nemaseti makuru nekubudirira uye kutora ruzivo rwakakosha kubva kune data redu.
