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())
