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Jun-te Kim 2025-10-23 08:06:04 +00:00
parent d849dae021
commit 59a23f7515
2 changed files with 36 additions and 19 deletions
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18
etl/month_end_automation_wave_3_layout.py
View file

@ -21,6 +21,7 @@ class BoardID(Enum):
_9660895490 = "NORTHUMBERLAND_COUNTY_SHDF_WAVE3"
_9641491000 = "WATFORD_WARM_HOMES"
_9671463094 = "SEDDON"
_9929454382 = "NCHA SHDF Wave 3 Main Operation Board"
board_ids = [
@ -30,6 +31,7 @@ board_ids = [
"9660895490", # Northumberland County SHDF Wave 3
"9641491000", # Watford Warm Homes
"9671463094", # Seddon
"9929454382", # NCHA SHDF Wave 3 Main Operation Board
]
empty = "Rate card info missing"
@ -53,6 +55,22 @@ rate_card_data_watford_warm_homes = {
}
rate_cards.update({"9641491000": pd.DataFrame(rate_card_data_watford_warm_homes)})
rate_card_data_ncha_wave_3 = {
"job_type": [
"RA", "ATT", "Coordination Stage 1 v1", "Coordination Stage 1 v2 remodel", "Coordination Stage 1 v3 remodel",
"Design Archetype Complex", "Design Archetype Simple", "Design Repetitive Simple", "Coordination Stage 2", "Lodgement phase 1", "Full lodgement phase 2",
"Post EPR", "Post EPC", "Post ATT", "retrofit evaluation",
"RA no show", "ATT no show", "post EPC no show", "Full cost MTP", "measure modelling", "design type not specified"
],
"rate": [
empty, empty, empty, empty, empty,
empty, empty, empty, empty, empty,
empty, empty, empty, empty, empty,
empty, empty, empty, empty, empty, check_with_andres
]
}
rate_cards.update({"9929454382": pd.DataFrame(rate_card_data_ncha_wave_3)})
rate_card_data_l_and_q_london = {

37
etl/month_end_automation_wave_accent_housing.py
View file

@ -172,27 +172,26 @@ final_df = None
if filtered_dfs:
final_df = pd.concat(filtered_dfs).reset_index(drop=True)
if final_df:
final_df["job_type"] = final_df["job_type"].str.lower()
rate_card_df["job_type"] = rate_card_df["job_type"].str.lower()
if final_df:
final_df["job_type"] = final_df["job_type"].str.lower()
rate_card_df["job_type"] = rate_card_df["job_type"].str.lower()
# Now perform the merge
combined_with_rates = final_df.merge(rate_card_df, on="job_type", how="left")
import datetime
timestamp = datetime.datetime.now().strftime('%Y-%m-%d_%H-%M')
# Now perform the merge
combined_with_rates = final_df.merge(rate_card_df, on="job_type", how="left")
import datetime
timestamp = datetime.datetime.now().strftime('%Y-%m-%d_%H-%M')
# Upload to sharepoint
attribute = ['address', 'client', 'job_type', 'rate']
master_folder_name = "2501 Accent housing"
file_name = f"{master_folder_name}_{timestamp}.xlsx"
combined_with_rates[attribute].to_excel(file_name, index=False)
# Upload to sharepoint
attribute = ['address', 'client', 'job_type', 'rate']
master_folder_name = "2501 Accent housing"
file_name = f"{master_folder_name}_{timestamp}.xlsx"
combined_with_rates[attribute].to_excel(file_name, index=False)
file_path = os.path.abspath(file_name)
file_path = os.path.abspath(file_name)
upload_to_month_end_folder(file_name, file_path, master_folder_name)
upload_to_month_end_folder(file_name, file_path, master_folder_name)
invoice_name = "rate_card.xlsx"
file_path = os.path.abspath(invoice_name)
rate_card_df.to_excel(invoice_name, index=False)
upload_to_month_end_folder(invoice_name, file_path, master_folder_name)
invoice_name = "rate_card.xlsx"
file_path = os.path.abspath(invoice_name)
rate_card_df.to_excel(invoice_name, index=False)
upload_to_month_end_folder(invoice_name, file_path, master_folder_name)