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33 lines
1.3 KiB
Python
33 lines
1.3 KiB
Python
import pandas as pd
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import numpy as np
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df1 = pd.DataFrame({'row': [0, 1, 2],
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'One_X': [1.1, 1.1, 1.1],
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'One_Y': [1.2, 1.2, 1.2],
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'Two_X': [1.11, 1.11, 1.11],
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'Two_Y': [1.22, 1.22, 1.22]})
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print(df1) ###line 8
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df2 = pd.DataFrame({'row': [0, 1, 2],
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'One_X': [1.1, 1.1, 1.1],
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'One_Y': [1.2, 1.2, 1.2],
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'Two_X': [1.11, 1.11, 1.11],
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'Two_Y': [1.22, 1.22, 1.22],
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'LABELS': ['A', 'B', 'C']})
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print(df2) ##line 16
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df3 = pd.DataFrame(data={'Province' : ['ON','QC','BC','AL','AL','MN','ON'],
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'City' : ['Toronto','Montreal','Vancouver','Calgary','Edmonton','Winnipeg','Windsor'],
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'Sales' : [13,6,16,8,4,3,1]})
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table = pd.pivot_table(df3,values=['Sales'],index=['Province'],columns=['City'],aggfunc=np.sum,margins=True)
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table.stack('City')
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print(df3)
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df4 = pd.DataFrame({'row': np.random.random(10000),
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'One_X': np.random.random(10000),
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'One_Y': np.random.random(10000),
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'Two_X': np.random.random(10000),
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'Two_Y': np.random.random(10000),
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'LABELS': ['A'] * 10000})
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print(df4) ##line 31
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