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import numpy as np
import pandas as pd
from pandas import DataFrame,Series
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arr1 = np.arange(9).reshape(3,3)
arr1
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np.concatenate([arr1,arr1],axis=1)
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np.concatenate([arr1,arr1],axis=0)
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ser1 = Series([0,1,2],index=['T','U','V'])
ser2 = Series([3,4],index=['X','Y'])
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ser1
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ser2
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pd.concat([ser1,ser2])
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# with 'axis=1' will produce a DataFrame
pd.concat([ser1,ser2],axis=1)
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# using index hierarchy
pd.concat([ser1,ser2],keys=['cat1','cat2'])
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df1 = DataFrame(np.random.randn(4,3),columns=['X','Y','Z'])
df1
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df2 = DataFrame(np.random.randn(3,3),columns=['Y','Q','X'])
df2
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pd.concat([df1,df2])
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# ignore indexes while concat
pd.concat([df1,df2],ignore_index=True)
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