def run_country_checker():
"""Checks for a valid country by checking df"""
while True:
try:
country = input(
text_color(
"What is your country? ",
text_type.QUESTION,
), )
country = country.lower()
country = country.title()
float(df[df.country == country]["purchasing_power_index"])
except TypeError:
print(
text_color(
f"'{country}' is an invalid country. Please try again.",
text_type.WARNING,
), )
else:
return country
def run_gender_checker():
"""Take valid gender from user"""
while True:
try:
gender = input(
text_color(
"What is your gender Male or Female? ",
text_type.QUESTION,
), )
gender = gender.lower()
if gender not in ["male", "female"]:
raise ValueError
except ValueError:
print(
text_color(
f"'{gender}' is an invalid Gender. Please try again",
text_type.WARNING,
), )
else:
return gender
def run_country_checker():
"""Checks for a valid country by checking df"""
while True:
try:
country = input(
text_color(
"What is your country? ",
text_type.QUESTION,
), )
country = country.lower()
country = country.title()
float(df[df.country == country]["purchasing_power_index"])
except TypeError:
ret = get_closest_country(country)
error_str = f"{country} is an invalid country or did you mean {ret}. Please try again."
if not ret:
error_str = f"{country} is an invalid country name. Please try again."
print(text_color(error_str, text_type.WARNING))
else:
return country
def safety_func():
"""finds your safety index"""
country_safety_index = float(
df[df.country == YOUR_COUNTRY]["safety_index"], )
print(
text_color(
f"In your country safety index is {country_safety_index}",
text_type.ANSWER,
), )
while True:
index_input = (input(
print_question('safety index', max_min_safety,
'higher is better'), ))
if isinstance(_value_checker(index_input), float):
return _value_checker(index_input)
elif _value_checker(index_input) == "default":
return country_safety_index
print(
text_color(
f"'{index_input}' is an invalid index. Please try again.",
text_type.WARNING,
), )
def pollution_func():
"""finds your pollution index"""
country_pollution_index = float(
df[df.country == YOUR_COUNTRY]["pollution_index"])
print(
text_color(
f"In your country pollution index is {country_pollution_index}",
text_type.ANSWER,
), )
while True:
index_input = input(
print_question("pollution index", max_min_pollution,
"lower is better"), )
if isinstance(_value_checker(index_input), float):
return _value_checker(index_input)
elif _value_checker(index_input) == "default":
return country_pollution_index
print(
text_color(
f"'{index_input}' is an invalid index. Please try again.",
text_type.WARNING,
), )
def format_info(column_title, value):
"""[summary]
Arguments:
column_title {[type]} -- [description]
value {[type]} -- [description]
Returns:
[type] -- [description]
"""
return text_color(
f"In your country {column_title} is {value}",
text_type.ANSWER,
)
def run_country_checker():
"""Checks for a valid country by checking df"""
while True:
try:
country = input(
text_color("What is your country? ", text_type.QUESTION))
country = country.lower()
country = country.title()
float(df[df.country == country]["purchasing_power_index"])
except TypeError:
# ret = get_closest_country(country)
# error_str = f"{country} is an invalid country or did you mean {ret}. Please try again."
# if not ret:
# error_str = f"{country} is an invalid country name. Please try again."
# print(text_color(error_str, text_type.WARNING))
similarCountries = []
for i in range(len(df)):
if (isSimilarTo(df['country'][i], country)):
similarCountries.append(df['country'][i])
if (len(similarCountries) == 0):
message = f"'{country} is an invalid country. Please try again."
else:
message = f"{country} is an invalid country. Did you mean "
for i in range(len(similarCountries)):
message += f"{similarCountries[i]}"
if (i != len(similarCountries) - 1):
message += " or "
else:
message += "?"
print(text_color(message, text_type.WARNING))
else:
return country
def health_care_func():
"""finds your health care index"""
country_health_care_index = float(
df[df.country == YOUR_COUNTRY]["health_care_index"],
)
print(
text_color(
f"In your country health care index is {country_health_care_index}",
text_type.ANSWER,
),
)
while True:
index_input = input(
print_question("health care index", max_min_health, mood="higher is better"),
)
if isinstance(_value_checker(index_input), float):
return _value_checker(index_input)
elif _value_checker(index_input) == "default":
return country_health_care_index
print(
text_color(f"'{index_input}' is an invalid index. Please try again."),
text_type.WARNING,
)
def ask_user_country(self):
"""Checks for a valid country by checking df."""
while True:
country_name = input(
text_color("What is your country? ", text_type.QUESTION), )
country_name = country_name.title()
try:
float(
self.countries_df[self.countries_df.country ==
country_name]["purchasing_power_index"],
)
except TypeError:
closest_country = self.get_closest_country(country_name)
error_str = f"{country_name} is an invalid country or did you mean {closest_country}. Please try again."
if not closest_country:
error_str = (
f"{country_name} is an invalid country name. Please try again."
)
print(text_color(error_str, text_type.WARNING))
else:
return country_name
def print_question(name_index, max_min_value, mood):
"""
Return a question that asks the user about the status of a factor
in his country, also displays the maximum and minimum value of this factor
in the world.
"""
if mood == 'higher is better':
first_value = max_min_value[0]
second_value = max_min_value[1]
elif mood == 'lower is better':
first_value = max_min_value[1]
second_value = max_min_value[0]
message = text_color(
f"What is your desirable {name_index} ({mood})? "
f"The best score in the world is "
f"{first_value[0]} "
f"({first_value[1]}), "
f"the worst is {second_value[0]} "
f"({second_value[1]}) ",
text_type.QUESTION,
)
return message
def format_question(name_index, max_min_value, mood):
"""Return a question that asks the user about the status of a factor in
his country.
Also displays the maximum and minimum value of this factor in
the world.
"""
if mood == "lower is better":
max_min_value = max_min_value[::-1]
best_value, best_value_country_name = max_min_value[0]
worst_value, worst_value_country_name = max_min_value[1]
message = text_color(
f"What is your desirable {name_index} ({mood})? "
f"The best score in the world is "
f"{best_value} "
f"({best_value_country_name}), "
f"the worst is {worst_value} "
f"({worst_value_country_name}) ",
text_type.QUESTION,
)
return message
your_cost_of_living_index = float(cost_of_living_func())
your_property_price_to_income_ratio = float(
property_price_to_income_ratio_func(), )
your_traffic_commute_time_index = float(traffic_commute_time_func())
your_pollution_index = float(pollution_func())
out_df = df[(df.purchasing_power_index > your_purchasing_power_index)
& (df.safety_index > your_safety_index) &
(df.health_care_index > your_health_care_index) &
(df.cost_of_living_index < your_cost_of_living_index) &
(df.property_price_to_income_ratio <
your_property_price_to_income_ratio) &
(df.traffic_commute_time_index <
your_traffic_commute_time_index) &
(df.pollution_index < your_pollution_index) &
(df.climate_index > your_climate_index)]
print_out_df = out_df[[
"country", "freedomhouse_score", "quality_of_life_index"
]].dropna().sort_values(by=['freedomhouse_score'], ascending=False)
if print_out_df.empty:
print(
text_color(f"There is no country better than {YOUR_COUNTRY}.", ),
text_type.ANSWER,
)
else:
with pd.option_context("display.max_rows", None, "display.max_columns",
None):
print(text_color(print_out_df, text_type.ANSWER))
desired: Dict[str, float] = PLACE2LIVE.desired_indexes
OUT_DF = DF[(DF.purchasing_power_index > desired["purchasing_power_index"])
& (DF.safety_index > desired["safety_index"])
& (DF.health_care_index > desired["health_care_index"])
& (DF.cost_of_living_index < desired["cost_of_living_index"])
& (DF.property_price_to_income_ratio <
desired["property_price_to_income_ratio"])
& (DF.traffic_commute_time_index <
desired["traffic_commute_time_index"])
& (DF.pollution_index < desired["pollution_index"])
& (DF.climate_index > desired["climate_index"])]
PRINT_OUT_DF = (OUT_DF[[
"country", "freedomhouse_score", "quality_of_life_index"
]].dropna().sort_values(by=["freedomhouse_score"], ascending=False))
if PRINT_OUT_DF.empty:
print(
text_color(
"There is no country better than {}.".format(
PLACE2LIVE.user_country_name),
text_type.ANSWER,
), )
else:
with pd.option_context("display.max_rows", None, "display.max_columns",
None):
print(
text_color(PRINT_OUT_DF.to_string(index=False),
text_type.ANSWER))
