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import pandas as pd
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
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
def create_fact_sales_order(dict_of_df):
df_sales = dict_of_df["sales_order"]
df_sales.index.name = "sales_record_id"
df_sales["created_date"] = pd.to_datetime(df_sales["created_at"]).dt.date
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",
"created_date",
"created_time",
"last_updated_date",
"last_updated_time",
"sales_staff_id",
"counterparty_id",
"units_sold",
"unit_price",
"currency_id",
"design_id",
"agreed_payment_date",
"agreed_delivery_date",
"agreed_delivery_location_id"
]]
return fact_sales_order
# 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
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