def uf_promesa_callback(proyecto, inmueble, etapa, year_values, month_values): if inmueble == 'Casa': fechas = dm.get_data_whithin_dates('neg', proyecto, inmueble, year_values, month_values, etapa) else: fechas = dm.get_data_whithin_dates('neg', proyecto, inmueble, year_values, month_values) count = fechas[fechas['Estado']=='Promesado']['Total Productos'].sum() count = np.round(count,2) return millify(count)
def get_personas_cot_mean(data, inmueble, proyecto, etapa=None): data = get_data(data, inmueble, proyecto, etapa) num_cot = [] for group, frame in data.groupby('RUT'): num_cot.append(frame.shape[0]) try: return app.millify(np.mean(num_cot)) except ValueError: return 'Error'
def right_cases_indicator_callback(data, inmueble, etapa, proyecto, year_values, month_values): if inmueble == 'Casa': data = dm.get_data_whithin_dates(data, proyecto, inmueble, year_values, month_values, etapa) else: data = dm.get_data_whithin_dates(data, proyecto, inmueble, year_values, month_values) num_cot = [] for group, frame in data.groupby('RUT'): num_cot.append(frame.shape[0]) try: return millify(np.mean(num_cot)) except ValueError: return 'Error'
def finance_indicator(mu, product, df, account): # source filtering if product != "all_s": df = df[df["Product"] == product] # period filtering if mu != "ALL": df = df[df["Market Unit"] == mu] df = df[df["Account"] == account] df = (df.groupby([pd.Grouper(key="Month") ]).sum().reset_index().sort_values("Month")) # if no results were found if df.empty: return 0 won = millify(str(df[df["Month"] == currentMonth()]["Amount"].sum())) return won
def indicator3_callback(market_unit, product, df): df = pd.read_json(df, orient="split") won = millify(str(df[df["IsWon"] == 1]["Amount"].count())) return dcc.Markdown("**{}**".format(won))
def right_opportunities_indicator_callback(df): df = pd.read_json(df, orient="split") lost = millify(str(df[(df["IsWon"] == 0) & (df["IsClosed"] == 1)]["Amount"].sum())) return lost
def middle_opportunities_indicator_callback(df): df = pd.read_json(df, orient="split") active = millify(str(df[(df["IsClosed"] == 0)]["Amount"].sum())) return active
def left_opportunities_indicator_callback(df): df = pd.read_json(df, orient="split") won = millify(str(df[df["IsWon"] == 1]["Amount"].sum())) return won
def left_opportunities_indicator_callback(df): df = pd.read_json(df, orient="split") won = millify(str(df[df["IsWon"] == 1]["Amount"].sum())) return dcc.Markdown("**{}**".format(won))
def middle_relac_indicator_callback(status): total_monto = 37e9 return millify(total_monto)
def left_relac_indicator_callback(status): return millify(db.cpe_mayo_2018.count())