def clients_closed(country, start=None, end=None, f=None, interval='month'):
g = [] if f is None else deepcopy(f)
g.append(Q('term', doctype='client'))
return _people_closed.df(country,
start=start,
end=end,
f=g,
interval=interval)
def df_start(country, start=None, end=None, f=None, interval='month'):
if f is None:
f = []
open = open_now(country, end=end, f=f)
opened = people_opened.df(country,
start=start,
end=end,
f=f,
interval=interval)
closed = people_closed.df(country,
start=start,
end=end,
f=f,
interval=interval)
if opened.empty or closed.empty:
return DataFrame(columns=['start'])
merged = opened.merge(closed, on='date', how='outer').sort_index()
merged = merged.fillna(0).astype('int64')
df = DataFrame(index=merged.index, columns=['start'])
if merged.empty:
return DataFrame(columns=['start'])
rev_idx = merged.index.tolist()
rev_idx.reverse()
for i in range(len(rev_idx)):
if i == 0:
df.loc[rev_idx[i]] = (open - merged['opened'].get(rev_idx[i], 0) +
merged['closed'].get(rev_idx[i], 0))
elif i > 0:
df.loc[rev_idx[i]] = (df.loc[rev_idx[i - 1]] -
merged['opened'].get(rev_idx[i], 0) +
merged['closed'].get(rev_idx[i], 0))
return df
def people_closed(country, start=None, end=None, f=None, interval='month'):
return _people_closed.df(country,
start=start,
end=end,
f=f,
interval=interval)
