pandas.DataFrame删除/选取含有特定数值的行或列实例

 import pandas as pd import numpy as np a=np.array([[1,2,3],[4,5,6],[7,8,9]]) df1=pd.DataFrame(a,index=['row0','row1','row2'],columns=list('ABC')) print(df1) df2=df1.copy() #删除/选取某列含有特定数值的行 #df1=df1[df1['A'].isin([1])] #df1[df1['A'].isin([1])] 选取df1中A列包含数字1的行 df1=df1[~df1['A'].isin([1])] #通过~取反，选取不包含数字1的行 print(df1)

 #删除/选取某行含有特定数值的列 cols=[x for i,x in enumerate(df2.columns) if df2.iat[0,i]==3] #利用enumerate对row0进行遍历，将含有数字3的列放入cols中 print(cols) #df2=df2[cols]  选取含有特定数值的列 df2=df2.drop(cols,axis=1) #利用drop方法将含有特定数值的列删除 print(df2)

 import pandas as pd import numpy as np df1 = pd.DataFrame( [ [np.nan, 2, np.nan, 0], [3, 4, np.nan, 1], [np.nan, np.nan, np.nan, 5], [np.nan, 3, np.nan, 4] ],columns=list('ABCD')) print(df1) df2=df1.copy() df1['A']=df1['A'].fillna('null') #将df中A列所有空值赋值为'null' print(df1) df1=df1[~df1['A'].isin(['null'])] print(df1) #删除某行空值所在列 df2[0:1]=df2[0:1].fillna('null') print(df2) cols=[x for i,x in enumerate(df2.columns) if df2.iat[0,i]=='null'] print(cols) df2=df2.drop(cols,axis=1) print(df2)