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no show re write

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Jun-te Kim 2025-07-28 16:14:18 +00:00
parent 7ee4bf5310
commit d1483fe072
14 changed files with 179 additions and 55 deletions
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80
etl/month_end_automation_wave_2_layout.py
View file

@ -9,9 +9,26 @@ import json
monday_key = "eyJhbGciOiJIUzI1NiJ9.eyJ0aWQiOjQ5ODc2ODQxOCwiYWFpIjoxMSwidWlkIjozNjE3ODAzNCwiaWFkIjoiMjAyNS0wNC0xMVQxMToyMzoxNy40NjdaIiwicGVyIjoibWU6d3JpdGUiLCJhY3RpZCI6MTM5OTc4MjMsInJnbiI6InVzZTEifQ.-2Lit4s46ZF6AXuMW9t0TxIaFLkHqD4Yo-PyM9i2XZY"
monday = MondayClient(monday_key)
# NCHK SHDF Westville Wave 1 & 2
# NCHA SHDF Westville Wave 1 & 2
board_ids = ["3900434153"]
rate_card_data = {
"job_type": [
"RA", "ATT", "Coordination Stage 1 v1", "Coordination Stage 1 v2 remodel", "Coordination Stage 1 v3 remodel",
"Design Archetype", "Design Repetitive", "Coordination Stage 2", "Lodgement phase 1", "Full lodgement phase 2",
"Post EPC", "Post ATT", "retrofit evaluation",
"RA no show", "ATT no show", "post EPC no show"
],
"rate": [
207.65, 101, 186.4, 98, 98,
450, 150, 163, 135, 120,
45, 90.5, 40,
25, 25, 25
]
}
rate_card_df = pd.DataFrame(rate_card_data)
for board in tqdm(board_ids):
board_data = monday.boards.fetch_boards_by_id(board)
@ -87,55 +104,69 @@ filtered_dfs.append(att)
v1 = df[
df["v1 coordination status"].str.lower().isin(["rc complete"])
].copy()
v1["job_type"] = "V1 Coordination"
v1["job_type"] = "Coordination Stage 1 v1"
filtered_dfs.append(v1)
# V2 Coordination
_ = df[df["v2 invoiced"].fillna('').str.lower().isin(['to be invoiced'])]
v2 = _[_["v2 dc/ima/pas"] > 0].copy()
v2["job_type"] = "V2 Coordination"
v2["job_type"] = "Coordination Stage 1 v2 remodel"
filtered_dfs.append(v2)
# V3 Coordination
v3 = df[
df["v3 invoiced"].str.lower().isin(["to be invoiced"])
].copy()
v3["job_type"] = "V3 Coordination"
v3["job_type"] = "Coordination Stage 1 v3 remodel"
filtered_dfs.append(v3)
# Design stage 1
# Coordination stage 2
cors2 = df[
df["rc stg. 2"].str.lower().isin(["to invoice", "completed"])
]
cors2["joby_type"] = "Coordination Stage 2"
filtered_dfs.append(cors2)
# Design type archietype
design1 = df[
df["design invoice status"].str.lower().isin(["to invoice"])
(df["design type for invoicing"].str.lower().isin(["archetype"])) & (df["design invoice status"].str.lower().isin(["to invoice"]))
].copy()
design1["job_type"] = "Design"
design1["job_type"] = "Design Archetype"
filtered_dfs.append(design1)
# Design stage 2
# design type reptitive
design1 = df[
(df["design type for invoicing"].str.lower().isin(["repetitive"])) & df["design invoice status"].str.lower().isin(["to invoice"])
].copy()
design1["job_type"] = "Design Repetitive"
filtered_dfs.append(design1)
# Design stage revisions
design2 = df[
df["revision 2 design invoice"].str.lower().isin(["to invoice"])
].copy()
design2["job_type"] = "Design Revision"
design2["job_type"] = "Design Repetitive"
filtered_dfs.append(design2)
# Lodgement Phase 1
lodg1 = df[
df["lodg. phase 1 invoice status"].str.lower().isin(["to invoice"])
].copy()
lodg1["job_type"] = "Lodgement Phase 1"
lodg1["job_type"] = "Lodgement phase 1"
filtered_dfs.append(lodg1)
# Full Lodgement Phase
lodg2 = df[
df["full lodgement invoice status"].str.lower().isin(["to invoice"])
].copy()
lodg2["job_type"] = "Full Lodgement"
lodg2["job_type"] = "Full Lodgement phase 2"
filtered_dfs.append(lodg2)
# POST EPC
post_epc = df[
df["post-epc status"].str.lower().isin(["epc pics uploaded"])
].copy()
post_epc["job_type"] = "POST EPC"
post_epc["job_type"] = "Post EPC"
filtered_dfs.append(post_epc)
@ -143,7 +174,7 @@ filtered_dfs.append(post_epc)
post_epr = df[
df["post-epc status"].str.lower().isin(["post epr completed"])
].copy()
post_epr["job_type"] = "POST ATT"
post_epr["job_type"] = "Post ATT"
filtered_dfs.append(post_epr)
@ -165,7 +196,8 @@ filtered_dfs.append(retro)
# RA NO Show
ra_ns = df[
df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)
(df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)) &
(df["ra no show evidence"] != 0)
].copy()
ra_ns["job_type"] = "RA NO SHOW"
filtered_dfs.append(ra_ns)
@ -174,7 +206,8 @@ filtered_dfs.append(ra_ns)
# ATT NO Show
att_ns = df[
df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)
(df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)) &
(df["att no show evidence"] != 0)
].copy()
att_ns["job_type"] = "ATT NO SHOW"
filtered_dfs.append(att_ns)
@ -182,11 +215,22 @@ filtered_dfs.append(att_ns)
# Post visit no show
epc_ns = df[
df["epc no show evidence"].fillna(-9999) != df["epc no show invoice"].fillna(-9999)
(df["epc no show evidence"].fillna(-9999) != df["epc no show invoice"].fillna(-9999)) &
(df["epc no show evidence"] != 0)
].copy()
epc_ns["job_type"] = "EPC NO SHOW"
epc_ns["job_type"] = "post EPC NO SHOW"
filtered_dfs.append(epc_ns)
final_df = pd.concat(filtered_dfs).reset_index(drop=True)
final_df[['address', 'client', 'job_type']]
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')
attribute = ['address', 'client', 'job_type', 'rate']
combined_with_rates[attribute].to_csv(f'NCHA SHDF Westville Wave 1 & 2_{timestamp}.csv', index=False)

6
etl/month_end_automation_wave_2_no_10.py
View file

@ -144,7 +144,8 @@ filtered_dfs.append(retro)
# RA NO Show
ra_ns = df[
df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)
(df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)) &
(df["ra no show evidence"] !=0 )
].copy()
ra_ns["job_type"] = "RA NO SHOW"
filtered_dfs.append(ra_ns)
@ -152,7 +153,8 @@ filtered_dfs.append(ra_ns)
# ATT NO Show
att_ns = df[
df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)
(df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)) &
(df["att no show evidence"] != 0)
].copy()
att_ns["job_type"] = "ATT NO SHOW"
filtered_dfs.append(att_ns)

3
etl/month_end_automation_wave_2_no_11.py
View file

@ -152,7 +152,8 @@ filtered_dfs.append(retro)
# ATT NO Show
att_ns = df[
df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)
(df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)) &
(df["att no show evidence"] != 0)
].copy()
att_ns["job_type"] = "ATT NO SHOW"
filtered_dfs.append(att_ns)

6
etl/month_end_automation_wave_2_no_12.py
View file

@ -141,7 +141,8 @@ filtered_dfs.append(retro)
# RA NO Show
ra_ns = df[
df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)
(df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)) &
(df["ra no show evidence"] != 0)
].copy()
ra_ns["job_type"] = "RA NO SHOW"
filtered_dfs.append(ra_ns)
@ -157,7 +158,8 @@ filtered_dfs.append(ra_ns)
# Post visit no show
epc_ns = df[
df["epc no show evidence"].fillna(-9999) != df["epc no show invoice"].fillna(-9999)
(df["epc no show evidence"].fillna(-9999) != df["epc no show invoice"].fillna(-9999)) &
(df["epc no show evidence"] != 0)
].copy()
epc_ns["job_type"] = "EPC NO SHOW"
filtered_dfs.append(epc_ns)

3
etl/month_end_automation_wave_2_no_13.py
View file

@ -140,7 +140,8 @@ filtered_dfs.append(retro)
# RA NO Show
ra_ns = df[
df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)
(df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)) &
(df["ra no show evidence"] != 0 )
].copy()
ra_ns["job_type"] = "RA NO SHOW"
filtered_dfs.append(ra_ns)

6
etl/month_end_automation_wave_2_no_14.py
View file

@ -143,7 +143,8 @@ filtered_dfs.append(retro)
# RA NO Show
ra_ns = df[
df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)
(df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)) &
(df["ra no show evidence"] != 0)
].copy()
ra_ns["job_type"] = "RA NO SHOW"
filtered_dfs.append(ra_ns)
@ -159,7 +160,8 @@ filtered_dfs.append(ra_ns)
# Post visit no show
epc_ns = df[
df["post epc no show evidence"].fillna(-9999) != df["post epc no show invoice"].fillna(-9999)
(df["post epc no show evidence"].fillna(-9999) != df["post epc no show invoice"].fillna(-9999)) &
(df["post epc no show evidence"] != 0)
].copy()
epc_ns["job_type"] = "EPC NO SHOW"
filtered_dfs.append(epc_ns)

9
etl/month_end_automation_wave_2_no_15.py
View file

@ -143,7 +143,8 @@ filtered_dfs.append(retro)
# RA NO Show
ra_ns = df[
df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)
(df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)) &
(df["ra no show evidence"] != 0)
].copy()
ra_ns["job_type"] = "RA NO SHOW"
filtered_dfs.append(ra_ns)
@ -151,7 +152,8 @@ filtered_dfs.append(ra_ns)
# ATT NO Show
att_ns = df[
df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)
(df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)) &
(df["att no show evidence"] != 0)
].copy()
att_ns["job_type"] = "ATT NO SHOW"
filtered_dfs.append(att_ns)
@ -159,7 +161,8 @@ filtered_dfs.append(att_ns)
# Post visit no show
epc_ns = df[
df["epc no show evidence"].fillna(-9999) != df["epc no show invoice"].fillna(-9999)
(df["epc no show evidence"].fillna(-9999) != df["epc no show invoice"].fillna(-9999)) &
(df["epc no show evidence"] != 0)
].copy()
epc_ns["job_type"] = "EPC NO SHOW"
filtered_dfs.append(epc_ns)

6
etl/month_end_automation_wave_2_no_16.py
View file

@ -143,7 +143,8 @@ filtered_dfs.append(retro)
# RA NO Show
ra_ns = df[
df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)
(df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)) &
(df["ra no show evidence"] != 0)
].copy()
ra_ns["job_type"] = "RA NO SHOW"
filtered_dfs.append(ra_ns)
@ -151,7 +152,8 @@ filtered_dfs.append(ra_ns)
# ATT NO Show
att_ns = df[
df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)
(df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)) &
(df["att no show evidence"] != 0)
].copy()
att_ns["job_type"] = "ATT NO SHOW"
filtered_dfs.append(att_ns)

9
etl/month_end_automation_wave_2_no_3.py
View file

@ -164,7 +164,8 @@ filtered_dfs.append(retro)
# RA NO Show
ra_ns = df[
df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)
(df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)) &
(df[" ra no show evidence"] != 0)
].copy()
ra_ns["job_type"] = "RA NO SHOW"
filtered_dfs.append(ra_ns)
@ -173,7 +174,8 @@ filtered_dfs.append(ra_ns)
# ATT NO Show
att_ns = df[
df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)
(df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)) &
(df["att no show evidence"] != 0)
].copy()
att_ns["job_type"] = "ATT NO SHOW"
filtered_dfs.append(att_ns)
@ -181,7 +183,8 @@ filtered_dfs.append(att_ns)
# Post visit no show
epc_ns = df[
df["post epc no show evidence"].fillna(-9999) != df["post epc no show invoice"].fillna(-9999)
(df["post epc no show evidence"].fillna(-9999) != df["post epc no show invoice"].fillna(-9999)) &
(df["post epc no show evidence"] != 0)
].copy()
epc_ns["job_type"] = "EPC NO SHOW"
filtered_dfs.append(epc_ns)

9
etl/month_end_automation_wave_2_no_4.py
View file

@ -160,7 +160,8 @@ filtered_dfs.append(retro)
# RA NO Show
ra_ns = df[
df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)
(df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)) &
(df["ra no show evidence"] != 0)
].copy()
ra_ns["job_type"] = "RA NO SHOW"
filtered_dfs.append(ra_ns)
@ -168,7 +169,8 @@ filtered_dfs.append(ra_ns)
# ATT NO Show
att_ns = df[
df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)
(df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)) &
(df["att no show evidence"] != 0)
].copy()
att_ns["job_type"] = "ATT NO SHOW"
filtered_dfs.append(att_ns)
@ -176,7 +178,8 @@ filtered_dfs.append(att_ns)
# Post visit no show
epc_ns = df[
df["post epc no show evidence"].fillna(-9999) != df["post epc no show invoice"].fillna(-9999)
(df["post epc no show evidence"].fillna(-9999) != df["post epc no show invoice"].fillna(-9999)) &
(df["post epc no show evidence"] != 0)
].copy()
epc_ns["job_type"] = "EPC NO SHOW"
filtered_dfs.append(epc_ns)

9
etl/month_end_automation_wave_2_no_5.py
View file

@ -160,7 +160,8 @@ filtered_dfs.append(retro)
# RA NO Show
ra_ns = df[
df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)
(df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)) &
(df["ra no show evidence"] != 0)
].copy()
ra_ns["job_type"] = "RA NO SHOW"
filtered_dfs.append(ra_ns)
@ -168,7 +169,8 @@ filtered_dfs.append(ra_ns)
# ATT NO Show
att_ns = df[
df["pre att no show evidence"].fillna(-9999) != df["pre att no show invoice"].fillna(-9999)
(df["pre att no show evidence"].fillna(-9999) != df["pre att no show invoice"].fillna(-9999)) &
(df["pre att no show evidence"] ! = 0)
].copy()
att_ns["job_type"] = "ATT NO SHOW"
filtered_dfs.append(att_ns)
@ -176,7 +178,8 @@ filtered_dfs.append(att_ns)
# Post visit no show
epc_ns = df[
df["epc no show evidence"].fillna(-9999) != df["epc no show invoice"].fillna(-9999)
(df["epc no show evidence"].fillna(-9999) != df["epc no show invoice"].fillna(-9999)) &
(df["epc no show evidence"] != 0 )
].copy()
epc_ns["job_type"] = "EPC NO SHOW"
filtered_dfs.append(epc_ns)

9
etl/month_end_automation_wave_2_no_7.py
View file

@ -143,7 +143,8 @@ filtered_dfs.append(retro)
# RA NO Show
ra_ns = df[
df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)
(df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)) &
(df["ra no show evidence"] != 0)
].copy()
ra_ns["job_type"] = "RA NO SHOW"
filtered_dfs.append(ra_ns)
@ -151,7 +152,8 @@ filtered_dfs.append(ra_ns)
# ATT NO Show
att_ns = df[
df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)
(df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)) &
(df["att no show evidence"] != 0 )
].copy()
att_ns["job_type"] = "ATT NO SHOW"
filtered_dfs.append(att_ns)
@ -159,7 +161,8 @@ filtered_dfs.append(att_ns)
# Post visit no show
epc_ns = df[
df["epc no show evidence"].fillna(-9999) != df["epc no show invoice"].fillna(-9999)
(df["epc no show evidence"].fillna(-9999) != df["epc no show invoice"].fillna(-9999)) &
(df["epc no show evidence"] != 0 )
].copy()
epc_ns["job_type"] = "EPC NO SHOW"
filtered_dfs.append(epc_ns)

73
etl/month_end_automation_wave_2_no_8.py
View file

@ -11,6 +11,23 @@ monday = MondayClient(monday_key)
# NCHA SHDF 2.1 SBS
board_ids = ["8668578700"]
rate_card_data = {
"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 EPC", "Post ATT", "retrofit evaluation",
"RA no show", "ATT no show", "post EPC no show"
],
"rate": [
259, 125, 280, 125, 125,
650, 415, 195, 175, 135,
120, 85, 125, 60,
25, 25, 25
]
}
rate_card_df = pd.DataFrame(rate_card_data)
for board in tqdm(board_ids):
board_data = monday.boards.fetch_boards_by_id(board)
@ -67,11 +84,12 @@ df = pd.DataFrame(all_records)
filtered_dfs = []
def get_df(df, column_name, success_critera, job_name):
def get_df(df, column_name, success_critera, job_name=None):
_ = df[
df[column_name].str.lower().isin(success_critera)
].copy()
_["job_type"] = job_name
if job_name:
_["job_type"] = job_name
return _
@ -87,21 +105,43 @@ filtered_dfs.append(att)
# V1 Coordination
v1 = get_df(df, "v1 coordination status".lower(), [
"rc complete",
], "V1 Coordination")
], "Coordination Stage 1 v1")
filtered_dfs.append(v1)
# V2 Coordination
v2 = get_df(df, "v2 coordination status", ["rc v2 complete", "uploaded"], "V2 Coordination")
v2 = get_df(df, "v2 coordination status", ["rc v2 complete", "uploaded"], "Coordination Stage 1 v2 remodel")
filtered_dfs.append(v2)
# # V3 Coordination
# v3 = get_df(df, "")
# # filtered_dfs.append(v3)
# Design stage 1
design1 = get_df(df, "rd invoiced", ["to invoice"], "Design")
# TODO check with Kevin [Coordination stage 2, design complex and revision]
# Corodination stage 2
cors2 = get_df(df, "rc stg. 2", ["to invoice"], "Coordination Stage 2")
filtered_dfs.append(cors2)
# Design Archtype Complex
design1 = get_df(df, "rd invoiced", ["to invoice"])
design1 = get_df(design1, "design type", ["archetype (complex)"])
design1 = get_df(design1, "design upload to sharepoint", ["done"], "Design Archetype Complex")
filtered_dfs.append(design1)
# Design Archtype Simple
design1 = get_df(df, "rd invoiced", ["to invoice"])
design1 = get_df(design1, "design type", ["archetype (simple)"])
design1 = get_df(design1, "design upload to sharepoint", ["done"], "Design Archetype Simple")
filtered_dfs.append(design1)
# Design Repitive Simple
design1 = get_df(df, "rd invoiced", ["to invoice"])
design1 = get_df(design1, "design type", ["Design Repetitive Simple"])
design1 = get_df(design1, "design upload to sharepoint", ["done"], "Design Repetitive Simple")
filtered_dfs.append(design1)
# TOOD Kevin:
# Check with Design checks and check with cor dination stage 2 checks
# Design revision
# design2 = get_df(df, "design revision invoice", [
# "Rev. A to invoice".lower(),
@ -120,7 +160,7 @@ lodg1 = get_df(df, "phase 1 to be invoiced".lower(), ["phase 1 to be invoiced"],
filtered_dfs.append(lodg1)
# Full Lodgement Phase
full_lodgement = get_df(df, "full lodgement invoice status".lower(), ["to be invoice"], "Full Lodgement")
full_lodgement = get_df(df, "full lodgement invoice status".lower(), ["to be invoice"], "Full Lodgement phase 2")
filtered_dfs.append(full_lodgement)
# POST EPC
@ -146,7 +186,8 @@ filtered_dfs.append(retro)
# RA NO Show
ra_ns = df[
df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)
(df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)) &
(df["ra no show evidence"] != 0 )
].copy()
ra_ns["job_type"] = "RA NO SHOW"
filtered_dfs.append(ra_ns)
@ -154,7 +195,8 @@ filtered_dfs.append(ra_ns)
# ATT NO Show
att_ns = df[
df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)
(df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)) &
(df["att no show evidence"] !=0 )
].copy()
att_ns["job_type"] = "ATT NO SHOW"
filtered_dfs.append(att_ns)
@ -169,4 +211,15 @@ filtered_dfs.append(att_ns)
final_df = pd.concat(filtered_dfs).reset_index(drop=True)
final_df[['address', 'client', 'job_type']]
final_df[['address', 'client', 'job_type']]
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')
attribute = ['address', 'client', 'job_type', 'rate']
combined_with_rates[attribute].to_csv(f'NCHA SHDF 2.1 SBS_{timestamp}.csv', index=False)

6
etl/month_end_automation_wave_2_no_9.py
View file

@ -143,7 +143,8 @@ filtered_dfs.append(retro)
# RA NO Show
ra_ns = df[
df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)
(df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)) &
(df["ra no show evidence"] != 0)
].copy()
ra_ns["job_type"] = "RA NO SHOW"
filtered_dfs.append(ra_ns)
@ -151,7 +152,8 @@ filtered_dfs.append(ra_ns)
# ATT NO Show
att_ns = df[
df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)
(df(df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999))) &
(df["att no show evidence"] != 0)
].copy()
att_ns["job_type"] = "ATT NO SHOW"
filtered_dfs.append(att_ns)