def test_load_cases_remote():
local = arcovid19.load_cases(url=LOCAL_CASES)
local = local[local.dates]
local[local.isnull()] = 143
remote = arcovid19.load_cases()
remote = remote[remote.dates]
remote[remote.isnull()] = 143
assert np.all(local == remote)
def test_plot_time_serie_all_equivalent_calls(fig_test, fig_ref):
cases = arcovid19.load_cases(cases_url=LOCAL_CASES,
areas_pop_url=LOCAL_AREA_POP)
# fig test
fig_test.set_size_inches(12, 12)
test_ax = fig_test.subplots()
cases.plot.time_serie_all(ax=test_ax)
test_ax.set_title("")
# expected
fig_ref.set_size_inches(12, 12)
exp_ax = fig_ref.subplots()
cases.plot.time_serie(deceased=False,
active=False,
recovered=False,
ax=exp_ax)
for prov in sorted(arcovid19.cases.CODE_TO_POVINCIA):
cases.plot.time_serie(prov,
deceased=False,
active=False,
recovered=False,
ax=exp_ax)
exp_ax.set_title("")
def test_plot_grate_full_period_all_equivalent_calls(fig_test, fig_ref):
cases = arcovid19.load_cases(url=LOCAL_CASES)
# fig test
fig_test.set_size_inches(12, 12)
test_ax = fig_test.subplots()
cases.plot.grate_full_period_all(ax=test_ax)
test_ax.set_title("")
# expected
fig_ref.set_size_inches(12, 12)
exp_ax = fig_ref.subplots()
cases.plot.grate_full_period(deceased=False,
active=False,
recovered=False,
ax=exp_ax)
for prov in sorted(arcovid19.CODE_TO_POVINCIA):
cases.plot.grate_full_period(prov,
deceased=False,
active=False,
recovered=False,
ax=exp_ax)
exp_ax.set_title("")
def test_full_grate_provincias():
df = arcovid19.load_cases(url=LOCAL_CASES)
for name, code in arcovid19.PROVINCIAS.items():
wname = df.grate_full_period(provincia=name)
wcode = df.grate_full_period(provincia=code)
assert isinstance(wname, pd.Series)
assert isinstance(wcode, pd.Series)
def test_restore_time_serie():
df = arcovid19.load_cases(url=LOCAL_CASES)
tsdf = df.restore_time_serie()
for prov in arcovid19.PROVINCIAS.values():
for code in arcovid19.STATUS.values():
orig_row = df.loc[(prov, code)][df.dates].values
ts = tsdf.loc[(prov, code)][df.dates].values
assert np.all(ts.cumsum() == orig_row)
def test_plot_boxplot(fig_test, fig_ref):
df = arcovid19.load_cases(url=LOCAL_CASES)
# fig test
test_ax = fig_test.subplots()
test_ax = df.plot("boxplot", ax=test_ax)
# expected
exp_ax = fig_ref.subplots()
df.plot.boxplot(ax=exp_ax)
def test_plot_time_serie(fig_test, fig_ref):
df = arcovid19.load_cases(url=LOCAL_CASES)
# fig test
test_ax = fig_test.subplots()
test_ax = df.plot("time_serie", ax=test_ax)
# expected
exp_ax = fig_ref.subplots()
df.plot.time_serie(ax=exp_ax)
def test_plot_grate_full_period(fig_test, fig_ref):
df = arcovid19.load_cases(url=LOCAL_CASES)
# fig test
test_ax = fig_test.subplots()
test_ax = df.plot("grate_full_period", ax=test_ax)
# expected
exp_ax = fig_ref.subplots()
df.plot.grate_full_period(ax=exp_ax)
def test_grate_provincias():
df = arcovid19.load_cases(url=LOCAL_CASES)
for name, code in arcovid19.PROVINCIAS.items():
wname = df.last_growth_rate(provincia=name)
wcode = df.last_growth_rate(provincia=code)
if np.isnan(wname):
assert np.isnan(wcode)
else:
assert wname == wcode
def test_plot_curva_epi_pais(fig_test, fig_ref):
df = arcovid19.load_cases(cases_url=LOCAL_CASES,
areas_pop_url=LOCAL_AREA_POP)
# fig test
test_ax = fig_test.subplots()
test_ax = df.plot("curva_epi_pais", ax=test_ax)
# expected
exp_ax = fig_ref.subplots()
df.plot.curva_epi_pais(ax=exp_ax)
def test_plot_time_serie_all(fig_test, fig_ref):
df = arcovid19.load_cases(cases_url=LOCAL_CASES,
areas_pop_url=LOCAL_AREA_POP)
# fig test
test_ax = fig_test.subplots()
test_ax = df.plot("time_serie_all", ax=test_ax)
# expected
exp_ax = fig_ref.subplots()
df.plot.time_serie_all(ax=exp_ax)
def test_plot_barplot(fig_test, fig_ref):
df = arcovid19.load_cases(cases_url=LOCAL_CASES,
areas_pop_url=LOCAL_AREA_POP)
# fig test
test_ax = fig_test.subplots()
test_ax = df.plot("barplot", ax=test_ax)
# expected
exp_ax = fig_ref.subplots()
df.plot.barplot(ax=exp_ax)
def test_plot_all_dates_ticks(plot_name):
df = arcovid19.load_cases(cases_url=LOCAL_CASES,
areas_pop_url=LOCAL_AREA_POP)
expected = [d.strftime(LABEL_DATE_FORMAT) for d in df.dates]
ax = df.plot(plot_name)
labels = [tlabel.get_text() for tlabel in ax.get_xticklabels()]
ticks = ax.get_xticks()
assert len(labels) == len(ticks)
assert labels == expected
def test_plot_all_dates_ticks(plot_name):
df = arcovid19.load_cases(url=LOCAL_CASES)
expected = [str(d.date()) for d in df.dates]
ax = df.plot(plot_name)
labels = [l.get_text() for l in ax.get_xticklabels()]
ticks = ax.get_xticks()
assert labels == expected
assert len(labels) == len(ticks)
def get_prc_df_arc19(url=arc19.CASES_URL, cached=True):
"""
"""
#
df_tmp = arc19.load_cases(cached=cached)
df_tmp.reset_index(inplace=True)
df_tmp.drop(['provincia_status', 'Pcia_status'], axis=1, inplace=True)
df_tmp.dropna(inplace=True)
# arc19 nos da los acumulados diarios
cmra_daily = {
'C': 'confirmados',
'R': 'recuperados',
'D': 'muertes',
'A': 'activos'
}
cmra_cumsum = {
'C': 'cumsum_confirmados',
'R': 'cumsum_recuperados',
'D': 'cumsum_muertes',
'A': 'cumsum_activos'
}
cmra_cumsum_list = list(cmra_cumsum)
cmra_daily_list = list(cmra_daily)
df_cat_list = []
for provincia in list(set(df_tmp.cod_provincia)):
#provincia='ARG'
df_tmp_prov = df_tmp[df_tmp.cod_provincia == provincia].T
status_names = df_tmp_prov.loc['cod_status'].to_dict()
df_tmp_prov.rename(columns=status_names, inplace=True)
df_tmp_prov.drop(['cod_provincia', 'cod_status'], inplace=True)
df_tmp_prov.reset_index(inplace=True)
df_tmp_prov['provincia'] = provincia
df_tmp_prov.rename(columns={'index': 'fecha'}, inplace=True)
df_tmp_prov['fecha'] = pd.to_datetime(
df_tmp_prov['fecha'].dt.strftime('%Y-%m-%d'))
d = df_tmp_prov[cmra_cumsum_list].diff()
d.loc[0] = df_tmp_prov[cmra_cumsum_list].loc[0]
d.rename(columns=cmra_daily, inplace=True)
df_prov = pd.concat([df_tmp_prov, d],
axis=1).rename(columns=cmra_cumsum)
df_cat_list.append(df_prov)
df_ = pd.concat(df_cat_list)
provDict = arc19.CODE_TO_POVINCIA
provDict.update({'ARG': 'Argentina_Nacion', 'BA': 'Buenos Aires'})
#
df_['provincia'] = df_['provincia'].map(provDict)
return df_
def test_load_cases_local():
df = arcovid19.load_cases(cases_url=LOCAL_CASES,
areas_pop_url=LOCAL_AREA_POP)
assert isinstance(df, arcovid19.cases.CasesFrame)
def test_delegation():
df = arcovid19.load_cases(cases_url=LOCAL_CASES,
areas_pop_url=LOCAL_AREA_POP)
assert repr(df) == repr(df.df)
assert df.transpose == df.df.transpose
def test_dates():
df = arcovid19.load_cases(url=LOCAL_CASES)
assert isinstance(df.dates, list)
def test_delegation():
df = arcovid19.load_cases(url=LOCAL_CASES)
assert repr(df) == repr(df.df)
assert df.transpose == df.df.transpose
def test_last_grate():
df = arcovid19.load_cases(url=LOCAL_CASES)
assert isinstance(df.last_growth_rate(), float)
def test_totcases():
df = arcovid19.load_cases(url=LOCAL_CASES)
assert isinstance(df.tot_cases, float)
def test_invalid_plot_name():
df = arcovid19.load_cases(cases_url=LOCAL_CASES,
areas_pop_url=LOCAL_AREA_POP)
with pytest.raises(ValueError):
df.plot("_plot_df")
# In[5]:
#hide_input
# CSV sources
local = True # if false import from arcovid
if local:
data_src_ = 'data/casos.xlsx'
#
df_ = get_prc_df_local(data_src_)
df_['provincia'] = df_['provincia'].apply(lambda x: provDict[x]
if x in provDict else x)
else:
data_src_ = arc19.CASES_URL
df_ = get_prc_df_arc19(url=data_src_, cached=True)
arc19.load_cases()
print('Importando desde: {}'.format(data_src_))
df_.head()
# ### Procesamiento
#
# Procesamos los datos y dejamos los mismos en el formato que seran utilizados en el reporte.
# In[6]:
#hide_input
ndays_ = -3
# Get cases
dft_cases = get_frame_unstack(df_, 'confirmados')
dft_deaths = get_frame_unstack(df_, 'muertes')
def test_get_item():
df = arcovid19.load_cases(cases_url=LOCAL_CASES,
areas_pop_url=LOCAL_AREA_POP)
value = df[df.provincia_status == "CBA_C"]
expected = df.df[df.provincia_status == "CBA_C"]
assert np.all(value == expected)
def test_grate_provincia_invalida():
df = arcovid19.load_cases(cases_url=LOCAL_CASES,
areas_pop_url=LOCAL_AREA_POP)
with pytest.raises(ValueError):
df.last_growth_rate(provincia="colorado")
def test_full_grate():
df = arcovid19.load_cases(cases_url=LOCAL_CASES,
areas_pop_url=LOCAL_AREA_POP)
assert isinstance(df.grate_full_period(), pd.Series)
def test_last_grate():
df = arcovid19.load_cases(cases_url=LOCAL_CASES,
areas_pop_url=LOCAL_AREA_POP)
assert isinstance(df.last_growth_rate(), float)
def test_areapop():
df = arcovid19.load_cases(cases_url=LOCAL_CASES,
areas_pop_url=LOCAL_AREA_POP)
assert np.all(df.areapop == df.extra["areapop"])
def test_dates():
df = arcovid19.load_cases(cases_url=LOCAL_CASES,
areas_pop_url=LOCAL_AREA_POP)
assert isinstance(df.dates, list)
def test_totcases():
df = arcovid19.load_cases(cases_url=LOCAL_CASES,
areas_pop_url=LOCAL_AREA_POP)
assert isinstance(df.tot_cases, float)
