import numpy as np import pandas as pd df = pd.read_csv('emp.csv') df 

#Series對(duì)象值替換s = df.iloc[2]#獲取行索引為2數(shù)據(jù)#單值替換s.replace('?',np.nan)#用np.nan替換？s.replace({'?':'NA'})#用NA替換？#多值替換s.replace(['?',r'$'],[np.nan,'NA'])#列表值替換s.replace({'?':np.nan,'$':'NA'})#字典映射#同缺失值填充方法類似s.replace(['?','$'],method='pad')#向前填充s.replace(['?','$'],method='ffill')#向前填充s.replace(['?','$'],method='bfill')#向后填充#limit參數(shù)控制填充次數(shù)s.replace(['?','$'],method='bfill',limit=1)#DataFrame對(duì)象值替換#單值替換df.replace('?',np.nan)#用np.nan替換？df.replace({'?':'NA'})#用NA替換？#按列指定單值替換df.replace({'EMPNO':'?'},np.nan)#用np.nan替換EMPNO列中?df.replace({'EMPNO':'?','ENAME':'.'},np.nan)#用np.nan替換EMPNO列中?和ENAME中.#多值替換df.replace(['?','.','$'],[np.nan,'NA','None'])##用np.nan替換？用NA替換. 用None替換$df.replace({'?':'NA','$':None})#用NA替換？ 用None替換$df.replace({'?','$'},{'NA',None})#用NA替換？ 用None替換$#正則替換df.replace(r'/?|/.|/$',np.nan,regex=True)#用np.nan替換？或.或$原字符df.replace([r'/?',r'/$'],np.nan,regex=True)#用np.nan替換？和$df.replace([r'/?',r'/$'],[np.nan,'NA'],regex=True)#用np.nan替換？用NA替換$符號(hào)df.replace(regex={r'/?':None})#value參數(shù)顯示傳遞df.replace(regex=[r'/?|/.|/$'],value=np.nan)#用np.nan替換？或.或$原字符