Data Science & ML Project |Garment Factory Analysis | Data Analysis Project using Python
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DATA DESCRIPTION
Our dataset belongs to the garment factory and workers focusing on their productivity.
We have considered “NUMBER OF STYLE CHANGE” column as a base column in each
of our machine learning model. It has only categorial data in it.
Below is the description of dataset columns:
1. Date : This column of the dataframe has date in MM-DD-YYYY
2. Day : This column of the dataframe has day of the Week
3. Quarter : A portion of the month. A month was divided into four quarters
4. Department : This column of the dataframe depicts associated department with the instance
5. Team_no : This column of the dataframe depicts Associated team number with the instance
6. No_of_workers : This column of the dataframe depicts Number of workers in each team
7. No_of_style_change : This column of the dataframe depicts Number of changes in the style of a
particular product
8. Targeted_productivity : This column of the dataframe depicts Targeted productivity set by the
Authority for each team for each day.
9. Smv : This column of the dataframe depicts Standard Minute Value, it is the allocated time for a
task.
10. Wip : This column of the dataframe depicts wip (Work in progress) which includes the number of
unfinished items for products
11. Over_time : This column of the dataframe represents the amount of overtime by each team in
minutes.
12. Incentive : This column of the dataframe represents the amount of financial incentive (in BDT)
that enables or motivates a particular course of action.
13. Idle_time : This column of the dataframe depicts the amount of time when the production was
interrupted due to several reasons
14. Idle_men : This column of the dataframe depicts the number of workers who were idle due to
production interruption
15. Actual_productivity : This column of the dataframe depicts the actual % of productivity that was
delivered by the workers. It ranges from 0-1
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