removed duplicate functions

1 files changed, 28 insertions, 89 deletions

diff --git a/src/dataframes.py b/src/dataframes.py
index 9ce3be0..380e4c5 100644
--- a/src/dataframes.py
+++ b/src/dataframes.py
@@ -1,11 +1,5 @@
 import pandas as pd
 from bs4 import BeautifulSoup
-from src.transform_lambda import read_from_s3_subfolder_to_df, tables
-from src.extract_lambda import extract_bucket
-import json
-import boto3
-import re
-from datetime import datetime as dt
 import requests
 
 #Table names:
@@ -21,8 +15,7 @@ import requests
 # dim_currency
 # dim_counterparty
 
-def create_dim_transaction(dict_of_df):
-    pass
+
 
 def create_fact_sales_order(dict_of_df):
     df_sales = dict_of_df["sales_order"]
@@ -31,8 +24,6 @@ def create_fact_sales_order(dict_of_df):
     df_sales["created_time"] = pd.to_datetime(df_sales["created_at"]).dt.time
     df_sales["last_updated_date"] = pd.to_datetime(df_sales["last_updated"]).dt.date
     df_sales["last_updated_time"] = pd.to_datetime(df_sales["last_updated"]).dt.time
-    pd.merge(dict_of_df["staff"], df_sales["sales_staff_id"], on="staff_id", how="left")
-    # df_sales.rename(columns={"staff_id": "sales_staff_id"})
     fact_sales_order = df_sales.loc[:,[
         "sales_record_id",
         "sales_order_id",
@@ -90,6 +81,11 @@ def create_fact_payment(dict_of_df):
     ]]
     return fact_payment
 
+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
+
 ## dim_location from address --> drops 2 columns
 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')
@@ -119,6 +115,20 @@ def create_dim_date(dict_of_df):
     df_date['quarter'] = df_date['date_id'].dt.quarter
     df_date.set_index('date_id')
 
+def create_dim_date(dict_of_df):
+    df_sales = dict_of_df["sales"]
+    df_sales = df_sales.loc[:, ["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_date = ["date_id", "year", "month", "day", "day_of_week", "day_name", "month_name", "quarter"]   #series.dt.quarter()
+    return dim_date
+
 def scrape_currency_names():
     response = requests.get('https://www.xe.com/currency/').content
     soup = BeautifulSoup(response,'html.parser')
@@ -130,107 +140,36 @@ def scrape_currency_names():
 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)
     return dim_cur
-
-
-
-
-
-
-
+#tests passed
 def create_dim_payment_type(dict_of_df):
     df_payment_type = dict_of_df["payment_type"]
     dim_payment_type = df_payment_type.loc[:, ["payment_type_id", "payment_type_name"]]
     return dim_payment_type
 
-def create_fact_payment(dict_of_df):
-    df_payment = dict_of_df["payment"]
-    df_payment.index.name = "payment_record_id"
-    df_payment["created_date"] = pd.to_datetime(df_payment["created_at"]).dt.date
-    df_payment["created_time"] = pd.to_datetime(df_payment["created_at"]).dt.time
-    df_payment["last_updated_date"] = pd.to_datetime(df_payment["last_updated"]).dt.date
-    df_payment["last_updated_time"] = pd.to_datetime(df_payment["last_updated"]).dt.time
-    fact_payment = df_payment.loc[:,[
-        "payment_record_id",
-        "payment_id",
-        "created_date",
-        "created_time",
-        "last_updated_date",
-        "last_updated_time",
-        "transaction_id",
-        "counterparty_id",
-        "payment_amount",
-        "currency_id",
-        "payment_type_id",
-        "paid",
-        "payment_date"
-    ]]
-    return fact_payment
-
+#tests passed
 def create_dim_design(dict_of_df):
     df_design = dict_of_df["design"]
     dim_design = df_design.loc[:, ["design_id", "design_name", "file_name", "file_location"]]
     return dim_design
-
+#tests passed
 def create_dim_staff(dict_of_df):
     staff_department = pd.merge(dict_of_df["staff"], dict_of_df["department"], on='department_id', how="left")
     dim_staff = staff_department.loc[:, ['staff_id', 'first_name', 'last_name', 'department_name', 'location', 'email_address']]
     return dim_staff
 
-def create_dim_currency(dict_of_df):
-    df_currency = dict_of_df["currency"]
-    dim_currency = df_currency.loc[:, ["currency_id", "currency_code"]]
-    mappings = {
-        "GBP": "Pound",
-        "USD": "US Dollar",
-        "EUR": "Euro"
-    }
-    dim_currency["currency_name"] = dim_currency["currency_code"].map(mappings)
-    return dim_currency
 
 
-def create_dim_date(dict_of_df):
-    df_sales = dict_of_df["sales"]
-    df_sales = df_sales.loc[:, ["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_date = ["date_id", "year", "month", "day", "day_of_week", "day_name", "month_name", "quarter"]   #series.dt.quarter()
-    return dim_date
 
 
-# TO DO:                                    
-# complete dim_date from merged fact table
-# merge dataframes into one dataframe
-# remove duplicates
-# test dim_date and fact_sales_order
-
-def create_sales_star_schema(dict_of_df):
-    dim_design = create_dim_design(dict_of_df)
-    dim_staff = create_dim_staff(dict_of_df)
-    dim_currency = create_dim_currency(dict_of_df)
-    dim_date = create_dim_date(dict_of_df)
-    
-    fact_sales_order = create_fact_sales_order(dict_of_df)
-    
-    fact_sales_order = fact_sales_order.merge(dim_design, on='design_id', how='left')
-    fact_sales_order = fact_sales_order.merge(dim_staff, left_on='sales_staff_id', right_on='staff_id', how='left')
-    fact_sales_order = fact_sales_order.merge(dim_currency, on='currency_id', how='left')
-    fact_sales_order = fact_sales_order.merge(dim_date, left_on='agreed_delivery_date', right_on='date_id', how='left')
-    
-    return fact_sales_order
 
 
 
-def create_dim_payment_type(dict_of_df):
-    df_payment_type = dict_of_df["payment_type"]
-    dim_payment_type = df_payment_type.loc[:, ["payment_type_id", "payment_type_name"]]
-    return dim_payment_type
+
+
+
+