# pandas_scd
executing slowly changing dimension type 2 on pandas dataframes
given pandas df of the source table, and pandas df of the target table, returning pandas df with the entire new target after scd2
## Installation
basic installtion :
pip install pandas-scd2
## Getting started
from pandas_scd import scd2
import pandas as df
tgt = pd.DataFrame.from_dict({'first_name': ["Chris"], 'last_name': ['Paul'], 'team': ["Clippers"], "start_ts": [datetime(2012, 1, 14, 3, 21, 34)], "end_ts": [None], "is_active": [True]})
src = pd.DataFrame.from_dict({'first_name': ["Chris"], 'last_name': ['Paul'], 'team': ['Suns']})
final_df = scd2(src, tgt)
tgt:
| first_name | last_name | team | start_ts | end_ts | is_active |
|------------|-----------|----------|---------------------|--------|-----------|
| Chris | Paul | Clippers | 2012-01-14 03:21:34 | | True |
src:
| first_name | last_name | team |
|------------|-----------|----------|
| Chris | Paul | Clippers |
final_df:
| first_name | last_name | team | start_ts | end_ts | is_active |
|------------|-----------|----------|---------------------|---------------------|-----------|
| Chris | Paul | Clippers | 2012-01-14 03:21:34 | 2018-01-01 00:00:00 | False |
| Chris | Paul | Suns | 2018-01-01 00:00:00 | | True |
**src:** pandas dataframe with the source of the SCD
**tgt:** pandas dataframe with the target of the SCD (target can be empty)
**cols_to_track:** list of columns to track changes (default is all columns from the source table)
**tz:** pytz time zone to use on start_ts and end_ts, default is None (will use local time)
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