# atlassianhw
<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->
A collection of simple functions to help with the homework.
## Install
``` sh
pip install atlassianhw
```
## How to use
Simple way to load in the data using `AData()`:
``` python
for name, data in AData().raw_data.items():
print(f'Data source: {name}')
display(data.head())
```
/Users/jasonorawe/Documents/py_wd/git/atlassianhw/atlassianhw/utils.py:22: FutureWarning: Inferring datetime64[ns] from data containing strings is deprecated and will be removed in a future version. To retain the old behavior explicitly pass Series(data, dtype=datetime64[ns])
'employee_details': pd.read_excel(pkgutil.get_data(__name__, '_data/Employee_details.xlsx')),
Data source: employee_details
Data source: glossary
Data source: manager_details
Data source: manager_mapping
Data source: promo_meta_data
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| | emp_id | Attrited | kudos_received_so_far | kudos_count_given_so_far | job_family | tenure_in_days_new | level | mnths_in_team | last_promotion_date |
|-----|--------|----------|-----------------------|--------------------------|----------------------|--------------------|-----------|---------------|---------------------|
| 0 | 1 | 0 | 5.157031 | 2 | Software Engineering | 1065 | Junior IC | 35.0 | 2022-10-01 |
| 1 | 2 | 0 | 5.466410 | 9 | Software Engineering | 1066 | Junior IC | 35.0 | 2022-04-01 |
| 2 | 3 | 0 | 4.744126 | 18 | Program Management | 1079 | Manager | 19.0 | 2021-07-16 |
| 3 | 4 | 1 | 0.261903 | 0 | Software Engineering | 154 | Director | 6.0 | 2020-03-30 |
| 4 | 5 | 0 | 5.918518 | 8 | Product Manager | 1079 | Manager | 35.0 | 2022-10-01 |
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| | Dataset | Dataset info | Column Name | Description |
|-----|------------------------|---------------------------|----------------------|------------------------------|
| 0 | promo_meta_data | historical promo metadata | level | level of employee |
| 1 | promo_meta_data | historical promo metadata | months_for_promotion | months for promotion in past |
| 2 | Manager_mapping | Manager mapping dataset | mgr_id | manager ID |
| 3 | Manager_mapping | Manager mapping dataset | emp_id | employee id |
| 4 | Attrition_Manager_info | Manager meta data | mgr_cum_churn_new | total churns under manager |
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| | mgr_id | mgr_cum_churn_new | Tenure_Mgr | total_teams_mgr | exp_as_mgr |
|-----|--------|-------------------|--------------------|-----------------|------------|
| 0 | 7582.0 | 0.000000 | 6-12 mons | 1.0 | 90.0 |
| 1 | 6132.0 | 6.136273 | 3-6 mons | 2.0 | 1489.0 |
| 2 | 7306.0 | 0.000000 | More Than 10 years | 2.0 | 1124.0 |
| 3 | 3712.0 | 2.899962 | 1-2 years | 8.0 | 579.0 |
| 4 | NaN | 0.000000 | 0 | 1.0 | 1489.0 |
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| | mgr_id | emp_id |
|-----|--------|--------|
| 0 | 7582.0 | 1 |
| 1 | 6132.0 | 2 |
| 2 | 7306.0 | 3 |
| 3 | 3712.0 | 4 |
| 4 | NaN | 5 |
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| | level | months_for_promotion |
|-----|-----------|----------------------|
| 0 | Junior IC | 37.0 |
| 1 | Junior IC | 40.0 |
| 2 | Manager | 30.0 |
| 3 | Director | 37.0 |
| 4 | Manager | 34.0 |
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