From 74be9f231ad560eed8630125045532b5975553dc Mon Sep 17 00:00:00 2001
From: T-Aji <tolujbd2@gmail.com>
Date: Wed, 21 Aug 2024 15:58:45 +0100
Subject: 5 dim tables created

---
 src/fact-sales-order.py | 48 +++++++++++++++++++++++++++++++++---------------
 1 file changed, 33 insertions(+), 15 deletions(-)

diff --git a/src/fact-sales-order.py b/src/fact-sales-order.py
index a143889..30c958f 100644
--- a/src/fact-sales-order.py
+++ b/src/fact-sales-order.py
@@ -11,7 +11,7 @@ df_address = dict_of_df[address]
 df_staff = dict_of_df[staff]
 df_department = dict_of_df[department]
 df_counterparty = dict_of_df[counterparty]
-
+df_sales = dict_of_df[sales]
 
 # creates the dim_design dataframe
 dim_design = df_design["design_id", "design_name", "file_name", "file_location"]
@@ -27,28 +27,46 @@ currency_names = pd.DataFrame(data=d)
 join_currency = pd.merge(df_currency, currency_names, on="currency_name", how="outer")
 dim_currency = join_currency["currency_id", "currency_code", "currency_name"]
 
-# creates the dim_location dataframe
-# need to change address id to location id 
-"dim_location dataframe: (location_id, address_line_1, address_line_2, district, city, postal code, country, phone)"
-dim_location = df_address["address_id", "address_line_1", "address_line_2", "district", "city", "postal_code" "country", "phone"]
-
-
-
+# Using .map to add currency_name column and link it to the currency code
+# dim_currency = df_currency["currency_id", "currency_code"]
+# mappings = {
+#     "GBP": "Pound",
+#     "USD": "US Dollar",
+#     "EUR": "Euro"
+# }
+# dim_currency["currency_name"] = dim_currency["currency_code"].map(mappings)
 
 
 
+# creates the dim_location dataframe
+# need to change address id to location id 
+"dim_location dataframe: (location_id, address_line_1, address_line_2, district, city, postal code, country, phone)"
+df_address.rename(columns={"address_id": "location_id"})
+dim_location = df_address["location_id", "address_line_1", "address_line_2", "district", "city", "postal_code" "country", "phone"]
 
+# creates the dim_counterparty dataframe
+counterparty_address = pd.merge(df_counterparty, df_address, left_on="legal_address_id", right_on='address_id', how="outer")
+counterparty_address.rename(columns={"address_line_1": "counterparty_legal_address_line_1", "address_line_2": "counterparty_legal_address_line_2",
+                                     "district": "counterparty_legal_district", "city": "counterparty_legal_city", "postal_code": "counterparty_postal_code",
+                                     "country": "counterparty_legal_country", "phone": "counterparty_legal_phone_number"})
 
+dim_counterparty = df_counterparty["counterparty_id", "counterparty_legal_name", "counterparty_legal_address_line_1",
+                                   "counterparty_legal_address_line_2", "counterparty_legal_district", "counterpart_legal_city",
+                                   "counterparty_legal_postal_code", "counterparty_legal_country", "counterparty_legal_phone_number"]
 
-# creates the dim_counterparty dataframe
-# counterparty_address = pd.merge(df_counterparty, df_address, left_on="legal_address_id", right_on='address_id', how="outer")
+# creates the dim_date dataframe
+df_sales = df_sales["agreed_delivery_date"]
+df_sales["agreed_delivery_date"] = pd.to_datetime["agreed_delivery_date"]
+df_sales["year"] = df_sales["agreed_delivery_date"].dt.year
+df_sales["month"] = df_sales["agreed_delivery_date"].dt.month
+df_sales["day"] = df_sales["agreed_delivery_date"].dt.day
+df_sales["day_of_week"] = df_sales["agreed_delivery_date"].dt.dayofweek
+df_sales["day_name"] = df_sales["agreed_delivery_date"].dt.day_name()
+df_sales["month_name"] = df_sales["agreed_delivery_date"].dt.month_name()
+df_sales["quarter"] = df_sales["agreed_delivery_date"].dt.quarter()
 
-# dim_counterparty = df_counterparty["counterparty_id", "counterparty_legal_name", "counterparty_legal_address_line_1",
-#                                    "counterparty_legal_address_line_2", "counterparty_legal_district", "counterpart_legal_city",
-#                                    "counterparty_legal_postal_code", "counterparty_legal_country", "counterparty_legal_phone_number"]
+dim_date = ["date_id", "year", "month", "day", "day_of_week", "day_name", "month_name", "quarter"]   #series.dt.quarter()
 
 
 # TO DO:
-# dim_location
-# dim_date
 # fact_sales_order
\ No newline at end of file
-- 
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