diff options
Diffstat (limited to 'src/dataframes.py')
| -rw-r--r-- | src/dataframes.py | 30 |
1 files changed, 16 insertions, 14 deletions
diff --git a/src/dataframes.py b/src/dataframes.py index 042c8aa..7d10aa7 100644 --- a/src/dataframes.py +++ b/src/dataframes.py @@ -81,28 +81,28 @@ def create_fact_payment(dict_of_df): ]] return fact_payment +#test passed def create_dim_transaction(dict_of_df): - df_transaction = dict_of_df["transaction"].drop(labels=['created_at', 'last_updated'], axis=1).set_index('transaction_id') - dim_transaction = df_transaction.loc[:, ["payment_type_id", "payment_type_name"]] - return dim_transaction + df_transaction = dict_of_df["transaction"].drop(labels=['created_at', 'last_updated'], axis=1) + return df_transaction -## dim_location from address --> drops 2 columns +#test passed def create_dim_location(dict_of_df): - df_loc = dict_of_df['address'].drop(labels=['created_at', 'last_updated'], axis=1).rename(columns={'address_id': 'location_id'}).set_index('location_id') + df_loc = dict_of_df['address'].drop(labels=['created_at', 'last_updated'], axis=1).rename(columns={'address_id': 'location_id'}) return df_loc -## dim_counterparty from address and counterparty + def create_dim_counterparty(dict_of_df): df_prefixed_address = dict_of_df['address'].add_prefix('counterparty_legal_', axis=1) df_cp = pd.merge(dict_of_df['counterparty'], df_prefixed_address, left_on="legal_address_id", - right_on="address_id", - how="outer").set_index('counterparty_id') + right_on="counterparty_legal_address_id", + how="outer") + df_cp.drop(columns=["legal_address_id","counterparty_legal_address_id"],inplace=True) return df_cp - -## dim_date from purchase_order +#test passed def create_dim_date(dict_of_df): fact_dfs = [create_fact_payment(dict_of_df), create_fact_purchase_orders(dict_of_df), create_fact_sales_order(dict_of_df)] date_col_names = [col_name for col_name in list(fact_dfs[0].columns) if 'date' in col_name] @@ -119,9 +119,10 @@ def create_dim_date(dict_of_df): df_date['day_of_week'] = df_date['date_id'].dt.dayofweek df_date['day_name'] = df_date['date_id'].dt.day_name() df_date['month_name'] = df_date['date_id'].dt.month_name() - df_date['quarter'] = df_date['date_id'].dt.quarter #By default, the DataFrame index is not included when uploading to RDS. We are not setting indexes to retain the column information - return + df_date['quarter'] = df_date['date_id'].dt.quarter + return df_date +#tests passed def scrape_currency_names(): response = requests.get('https://www.xe.com/currency/').content soup = BeautifulSoup(response,'html.parser') @@ -130,11 +131,12 @@ def scrape_currency_names(): df_cur = sr.str.split(pat=" - ",expand=True).rename({0:'currency_code',1:'currency_name'},axis=1) return df_cur +#tests passed def create_dim_currency(dict_of_df,names=scrape_currency_names()): df_cur = dict_of_df['currency'].drop(labels=['created_at', 'last_updated'], axis=1) - dim_cur = pd.merge(df_cur,names,left_on='currency_code',right_on='currency_code',how='inner').set_index('currency_id') - print(dim_cur) + dim_cur = pd.merge(df_cur,names,left_on='currency_code',right_on='currency_code',how='inner') return dim_cur + #tests passed def create_dim_payment_type(dict_of_df): df_payment_type = dict_of_df["payment_type"] |