import numpy as np import pandas as pd x=np.array([1,2,3]).reshape(1,3)#调节形状为二维数组 y=np.array([4,5,6]).reshape(1,3) z=np.array([7,8,9]).reshape(1,3) print(np.concatenate([x,y,z]))#numpy二维数组的拼接 arr1=np.random.randn(4,4) np.concatenate([arr1,arr1])#横着拼接 np.concatenate([arr1,arr1],axis=1)#竖着拼接 def make_dataFrame(cols,ind): data={c:[str(c)+str(i) for i in ind] for c in cols} return pd.DataFrame(data,ind) print(make_dataFrame("abc",range(3))) df1=make_dataFrame("AB",[1,2]) df2=make_dataFrame("AB",[3,4]) print(pd.concat([df1,df2])) print(pd.concat([df1,df2],ignore_index=True))#覆盖原索引,重建索引 print(pd.concat([df1,df2],keys=["M","N"]))#增加索引 s1=pd.Series(["a","b","c"],index=[1,2,3]) s2=pd.Series(["e","f","g"],index=[4,5,6]) print(pd.concat([s1,s2]))
import numpy as np import pandas as pd import tushare as ts stock600848=ts.get_hist_data('600848') stock600898=ts.get_hist_data('600898') stock600898price=stock600898[["open","high","close","low"]].head(5) stock600848price=stock600848[["open","high","close","low"]].head(5) print(pd.concat([stock600898price,stock600848price],keys=["600848","600898"]))