planner/webservice/marketing_plan.py

import pandas as pd
import numpy as np
from pathlib import Path
import json


base_dir = Path(__file__).parent.parent
filename = base_dir / "data" / "Marketingplanung_AHR_2023_V1.xls"
output = base_dir / "export" / "marketing_2023.json"
output_csv = base_dir / "export" / "marketing_2023.csv"
debug_csv = base_dir / "export" / "marketing_2023_rest.csv"

department = {" MM": "10", " ULM": "40", " LL": "50", "KRU": "30", "GZ": "55", "AAM": "82", "AAM-MOT": "81"}

columns = [
    "Bezeichnung",
    "Segment",
    "Termin",
    "Wert1",
    "Wert2",
    "Wert3",
    "Wert4",
    "Wert5",
    "Wert6",
    "Wert7",
    "Wert8",
    "Wert9",
    "Wert10",
    "Wert11",
    "Wert12",
    "Summe",
]

defaults = ["", "", "", 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
types = [str] * 3  # + [float] * 13

xls = pd.read_excel(
    filename,
    sheet_name=list(department.keys()),
    skiprows=4,
    usecols="A:P",
    names=columns,
    converters=dict(zip(columns, types)),
)
xls_temp = []

for sheet, dept_no in department.items():
    xls[sheet]["Betrieb Nr"] = dept_no
    xls[sheet] = xls[sheet].fillna(value=dict(zip(columns, defaults)))
    xls[sheet]["Konto Nr"] = np.where(
        xls[sheet]["Segment"].str.startswith("Kto "), xls[sheet]["Segment"].str.slice(4, 9), "Rest"
    )
    # xls[sheet]['Konto Nr'] = np.where(xls[sheet]['Segment'].str.startswith('50% '),
    # xls[sheet]['Segment'].str.slice(-5), xls[sheet]['Konto Nr'])
    temp = xls[sheet][xls[sheet]["Segment"].str.startswith("50% ")].copy()
    temp["Konto Nr"] = temp["Segment"].str.slice(8, 13)
    xls_temp.append(temp)
    temp2 = temp.copy()
    temp2["Konto Nr"] = temp2["Segment"].str.slice(-5)
    xls_temp.append(temp2)

xls_temp_concat = pd.concat(xls_temp)
for c in columns[3:]:
    xls_temp_concat[c] = xls_temp_concat[c] * 0.5

df = pd.concat(list(xls.values()) + [xls_temp_concat])

df_rest = df[(df["Konto Nr"] == "Rest") & (df["Summe"] != 0)]
df_rest.to_csv(debug_csv, sep=";", decimal=",")
df = df[df["Konto Nr"] != "Rest"]

df["Wert11"] = df["Wert11"].astype(float)
df["Wert12"] = df["Wert12"].astype(float)

for c in columns[3:]:
    df[c] = df[c].round()
df = df.drop(labels=["Summe"], axis=1)

df = df.groupby(["Konto Nr", "Betrieb Nr"]).sum()
print(df.info())
# df.reset_index(inplace=True)

df.to_csv(output_csv, sep=";", decimal=",")
dict_split = df.to_dict(orient="split")

res = {}
for index, data in zip(dict_split["index"], dict_split["data"]):
    kto, dept = index
    if kto not in res:
        res[kto] = {}
    res[kto][dept] = data

json.dump(res, open(output, "w"), indent=2)