piper.verbs.inner_join¶
-
piper.verbs.inner_join(df: pandas.core.frame.DataFrame, *args, **kwargs) → pandas.core.frame.DataFrame[source]¶ df (All) | df2 (All) matching records only
This is a wrapper function rather than using e.g. df.merge(how=’inner’) For details of args, kwargs - see help(pd.DataFrame.merge)
Examples
order_data = {'OrderNo': [1001, 1002, 1003, 1004, 1005], 'Status': ['A', 'C', 'A', 'A', 'P'], 'Type_': ['SO', 'SA', 'SO', 'DA', 'DD']} orders = pd.DataFrame(order_data) status_data = {'Status': ['A', 'C', 'P'], 'description': ['Active', 'Closed', 'Pending']} statuses = pd.DataFrame(status_data) order_types_data = {'Type_': ['SA', 'SO'], 'description': ['Sales Order', 'Standing Order'], 'description_2': ['Arbitrary desc', 'another one']} types_ = pd.DataFrame(order_types_data) %%piper orders >> inner_join(types_, suffixes=('_orders', '_types')) | OrderNo | Status | Type_ | description | description_2 | |----------:|:---------|:--------|:---------------|:----------------| | 1001 | A | SO | Standing Order | another one | | 1003 | A | SO | Standing Order | another one | | 1002 | C | SA | Sales Order | Arbitrary desc |
- Parameters
df – dataframe
*args – arguments for wrapped function
**kwargs – keyword-parameters for wrapped function
- Returns
- Return type
A pandas DataFrame