03Inconsistency

Class Inconsistency¶

A notebook to showcase the usage of Inconsistency class

In [1]:

# import class
from blueautomata.inconsistency import Inconsistency
import pandas as pd

# import class from blueautomata.inconsistency import Inconsistency import pandas as pd

In [2]:

preview = pd.read_excel('data/fakesystem/experiment/sample1.xlsx')
preview.head()

preview = pd.read_excel('data/fakesystem/experiment/sample1.xlsx') preview.head()

Out[2]:

	Name	Cube
0	Christopher bt Bruce	Iron
1	Michael perez	Bronze
2	Stephanie ccarr	Metal
3	Julia bin Vargas	Silver
4	Michelle WalKer	Gold

• The correct name should be Christopher Bruce, Michael Perez, Stephanie Carr, Julia Vargas and Michelle Walker according to the staff data.

In [3]:

test = Inconsistency(
    filepath="data/fakesystem/experiment/sample1.xlsx",
    staff_data="data/fake_hr_data.xlsx",
    checklist="data/checklist.xlsx",
    sheet_number=0,
)

df = test.fix_inconsistency()

df.head()

test = Inconsistency( filepath="data/fakesystem/experiment/sample1.xlsx", staff_data="data/fake_hr_data.xlsx", checklist="data/checklist.xlsx", sheet_number=0, ) df = test.fix_inconsistency() df.head()

Out[3]:

	Department	Dept	User ID	Name	System1	Cube
0	Google	GOOG	EWBZM6YV67W33MXY9	Christopher Bruce	KLSE	Iron
1	Apple	AAPL	WRZZDUR66UZWVB0DH	Michael Perez	KLSE	Bronze
2	Apple	AAPL	AURG7K1RXGMNSYLSV	Stephanie Carr	KLSE	Metal
3	Apple	AAPL	99TTCX5T43R1RRWR1	Michelle Walker	KLSE	Gold
4	Apple	AAPL	2U5PJRW18MG4XGATV	David Carpenter	KLSE	Titanium

• You can see that the name of the persons are being fixed

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Last update: 2023-09-07
Created: 2023-09-07