pandas dataframe 新增行和列
阿新 • • 發佈:2018-11-15
import numpy as np import pandas as pd df=pd.DataFrame(np.random.randn(3,4),columns=list("ABCD"),index=list("xyz")) # print(df) res1=df.apply(lambda x:x.sum()) # print(res1) # print(type(res1)) #<class 'pandas.core.series.Series'> #新增行 df.loc['newrow']=res1 # print(df) #新增列 res2=df.apply(lambda x:x.sum(),axis=1) # print(res2) df['newcolumn']=res2 # print(df) ''' apply 函式 官網 ''' df = pd.DataFrame([[4, 9],] * 3, columns=['A', 'B']) # print(df.apply(np.sqrt)) df[['new1','new2']]=df.apply(np.sqrt) print(df) # df.loc['newr1','newr2','new3']= df.apply(np.sqrt,axis=1)
res=df.apply(np.sqrt,axis=1) #<class 'pandas.core.frame.DataFrame'> print(res) df=pd.concat([res,df]) print(df)