Merge branch 'development' into feature/load-lambda-tests

1 files changed, 26 insertions, 59 deletions

diff --git a/src/dataframes.py b/src/dataframes.py
index 43facd6..ab32fff 100644
--- a/src/dataframes.py
+++ b/src/dataframes.py
@@ -20,9 +20,7 @@ import requests
 def create_fact_sales_order(dict_of_df):
     df_sales = dict_of_df["sales_order"]
     df_sales.index.name = "sales_record_id"
-
-
-<< << << < HEAD
+    
     df_sales["created_date"] = df_sales["created_at"].astype(
         "datetime64[ns]").dt.date
     df_sales["created_time"] = (
@@ -33,17 +31,6 @@ def create_fact_sales_order(dict_of_df):
     )
     df_sales["last_updated_time"] = (
         df_sales["last_updated"].astype("datetime64[ns]").dt.floor("s").dt.time
-== == == =
-    df_sales["created_date"]=pd.to_datetime(
-        df_sales["created_at"], format="%Y-%m-%d")
-    df_sales["created_time"]=pd.to_datetime(
-        df_sales["created_at"], format="%H-%M-%S")
-    df_sales["last_updated_date"]=pd.to_datetime(
-        df_sales["last_updated"], format="%Y-%m-%d"
-    )
-    df_sales["last_updated_time"]=pd.to_datetime(
-        df_sales["last_updated"], format="%H-%M-%S"
->> >>>> > 5db3f61(style: format code with Autopep8, Black and Ruff Formatter)
     )
     df_sales["agreed_delivery_date"]=pd.to_datetime(
         df_sales["agreed_delivery_date"], format="%Y-%m-%d"
@@ -51,11 +38,28 @@ def create_fact_sales_order(dict_of_df):
     df_sales["agreed_payment_date"]=pd.to_datetime(
         df_sales["agreed_payment_date"], format="%Y-%m-%d"
     )
-<< << << < HEAD
     df_sales=df_sales.drop(labels=["created_at", "last_updated"], axis=1)
-== == == =
-    df_sales.drop(labels=["created_at", "last_updated"], axis=1, inplace=True)
->> >>>> > 5db3f61(style: format code with Autopep8, Black and Ruff Formatter)
+
+    df_sales.reset_index(inplace=True)
+    return df_sales
+
+    df_sales["created_date"] = df_sales["created_at"].astype("datetime64[ns]").dt.date
+    df_sales["created_time"] = (
+        df_sales["created_at"].astype("datetime64[ns]").dt.floor("s").dt.time
+    )
+    df_sales["last_updated_date"] = (
+        df_sales["last_updated"].astype("datetime64[ns]").dt.date
+    )
+    df_sales["last_updated_time"] = (
+        df_sales["last_updated"].astype("datetime64[ns]").dt.floor("s").dt.time
+    )
+    df_sales["agreed_delivery_date"] = pd.to_datetime(
+        df_sales["agreed_delivery_date"], format="%Y-%m-%d"
+    )
+    df_sales["agreed_payment_date"] = pd.to_datetime(
+        df_sales["agreed_payment_date"], format="%Y-%m-%d"
+    )
+    df_sales = df_sales.drop(labels=["created_at", "last_updated"], axis=1)
     df_sales.reset_index(inplace=True)
     return df_sales
 
@@ -66,7 +70,6 @@ def create_fact_sales_order(dict_of_df):
 def create_fact_purchase_orders(dict_of_df):
     df_po=dict_of_df["purchase_order"]
     df_po.index.name="purchase_record_id"
-<< << << < HEAD
     df_po["created_date"]=df_po["created_at"].astype("datetime64[ns]").dt.date
     df_po["created_time"]=(
         df_po["created_at"].astype("datetime64[ns]").dt.floor("s").dt.time
@@ -75,17 +78,7 @@ def create_fact_purchase_orders(dict_of_df):
         "datetime64[ns]").dt.date
     df_po["last_updated_time"]=(
         df_po["last_updated"].astype("datetime64[ns]").dt.floor("s").dt.time
-== == == =
-    df_po["created_date"]=pd.to_datetime(
-        df_po["created_at"], format="%Y-%m-%d")
-    df_po["created_time"]=pd.to_datetime(
-        df_po["created_at"], format="%H-%M-%S")
-    df_po["last_updated_date"]=pd.to_datetime(
-        df_po["last_updated"], format="%Y-%m-%d"
-    )
-    df_po["last_updated_time"]=pd.to_datetime(
-        df_po["last_updated"], format="%H-%M-%S"
->> >>>> > 5db3f61(style: format code with Autopep8, Black and Ruff Formatter)
+
     )
     df_po["agreed_delivery_date"]=pd.to_datetime(
         df_po["agreed_delivery_date"], format="%Y-%m-%d"
@@ -93,11 +86,7 @@ def create_fact_purchase_orders(dict_of_df):
     df_po["agreed_payment_date"]=pd.to_datetime(
         df_po["agreed_payment_date"], format="%Y-%m-%d"
     )
-<< << << < HEAD
     df_po=df_po.drop(labels=["created_at", "last_updated"], axis=1)
-== == == =
-    df_po.drop(labels=["created_at", "last_updated"], axis=1, inplace=True)
->> >>>> > 5db3f61(style: format code with Autopep8, Black and Ruff Formatter)
     df_po.reset_index(inplace=True)
     return df_po
 
@@ -108,7 +97,6 @@ def create_fact_purchase_orders(dict_of_df):
 def create_fact_payment(dict_of_df):
     df_payment=dict_of_df["payment"]
     df_payment.index.name="payment_record_id"
-<< << << < HEAD
     df_payment["created_date"]=(
         df_payment["created_at"].astype("datetime64[ns]").dt.date
     )
@@ -121,29 +109,12 @@ def create_fact_payment(dict_of_df):
     df_payment["last_updated_time"]=(
         df_payment["last_updated"].astype(
             "datetime64[ns]").dt.floor("s").dt.time
-== == == =
-    df_payment["created_date"]=pd.to_datetime(
-        df_payment["created_at"], format="%Y-%m-%d"
-    )
-    df_payment["created_time"]=pd.to_datetime(
-        df_payment["created_at"], format="%H-%M-%S"
-    )
-    df_payment["last_updated_date"]=pd.to_datetime(
-        df_payment["last_updated"], format="%Y-%m-%d"
-    )
-    df_payment["last_updated_time"]=pd.to_datetime(
-        df_payment["last_updated"], format="%H-%M-%S"
->> >>>> > 5db3f61(style: format code with Autopep8, Black and Ruff Formatter)
     )
     df_payment["payment_date"]=pd.to_datetime(
         df_payment["payment_date"], format="%Y-%m-%d"
     )
-<< << << < HEAD
     df_payment=df_payment.drop(labels=["created_at", "last_updated"], axis=1)
-== == == =
-    df_payment.drop(
-        labels=["created_at", "last_updated"], axis=1, inplace=True)
->> >>>> > 5db3f61(style: format code with Autopep8, Black and Ruff Formatter)
+    
     df_payment.reset_index(inplace=True)
     return df_payment
 
@@ -196,14 +167,10 @@ def create_dim_date(dict_of_df):
         create_fact_purchase_orders(dict_of_df),
         create_fact_sales_order(dict_of_df),
     ]
-    list_of_date_columns=[]
+    list_of_date_columns = []
     for df in fact_dfs:
-        date_col_names=[
-<< << << < HEAD
+        date_col_names = [
             col_name for col_name in list(df.columns) if "_date" in col_name
-== == == =
-            col_name for col_name in list(df.columns) if "date" in col_name
->> >>>> > 5db3f61(style: format code with Autopep8, Black and Ruff Formatter)
         ]
         for col in date_col_names:
             list_of_date_columns.append(df[col])