python pandas slice columns

1 ImportPandas as PD2DF1 = PD. DataFrame ([[1,2,3],[5,6,7],[3,9,0],[8,0,3]],columns=['X1','X2','X3'])3DF2 = PD. DataFrame ([[1,2],[4,6],[3,9]],columns=['X1','X4'])4 Print(DF1)5 Print(DF2)6DF3 = Pd.merge (df1,df2,how =' Left', on='X1')7 Print(DF3)8DF4 = Pd.merge (df1,df2,how =' Right', on='X1')9 Print(DF4)TenDf5 = Pd.merge (df1,df2,how ='Inner', on='X1') One Print(DF5) ADf6 = Pd.merge (df1,df2,how ='outer',

This article brings the content is about Python pandas in-depth understanding (code example), there is a certain reference value, the need for friends can refer to, I hope to help you. First, screening First, create a 6X4 matrix data. Dates = Pd.date_range (' 20180830 ', periods=6) df = PD. DataFrame (Np.arange) reshape ((6,4)), index=dates, columns=[' A ', ' B

ImportOSImportPandas as PDImportMatplotlib.pyplot as PltdefTest_run (): start_date='2017-01-01'End_data='2017-12-15'dates=Pd.date_range (start_date, End_data)#Create an empty data frameDF=PD. DataFrame (index=dates) Symbols=['SPY','AAPL','IBM','GOOG','GLD'] forSymbolinchsymbols:temp=getadjcloseforsymbol (symbol) DF=df.join (temp, how='Inner') returnDF def Normalize_data (DF): "" " normalize stock prices using the first row of the DATAFR Ame " " " df=df/df.ix[0,:] return DF defGetadj