def q2(dic):
print("Question 2:")
dic_winter, dic_not_winter = data.filter_by_feature(dic, "season", {2})
dic_is_holiday, dic_not_holiday = data.filter_by_feature(dic_winter, "is_holiday", {0})
print("is", dic_not_holiday)
methods = [statistics.mean, statistics.median]
print("If t1<=13.0, then:")
statistics.population_statistics("Winter holiday records:", dic_is_holiday, "t1", "cnt", 13.0, False, methods)
statistics.population_statistics("Winter weekday records:", dic_not_holiday, "t1", "cnt", 13.0, False, methods)
def main(argv):
"""
Main function of the program
:param argv: argv[0] = /home/student/your_path/main.py, argv[1] = /home/student/your_path/ london.csv,
argv[2] = "hum, t1, cnt, season, is_holiday"
:return: none
"""
# question 1
data_dict = data.load_data(argv[1], argv[2])
statistic_functions = [
statistics.sum_f, statistics.mean, statistics.median
]
print("Question 1:")
feature_list = ["hum", "t1", "cnt"]
data_name, data_not_name = data.filter_by_value(data_dict, 'season', {1})
data.print_details(data_name, feature_list, statistic_functions, 'Summer')
data_name, data_not_name = data.filter_by_value(data_dict, 'is_holiday',
{1})
data.print_details(data_name, feature_list, statistic_functions, 'Holiday')
data.print_details(data_dict, feature_list, statistic_functions, 'All')
print() # before question 2
# question 2
print("Question 2:")
is_above = 0
title_list = ["Winter holiday records:", "Winter weekday records:"]
print("If t1<=13.0, then:")
data_winter, data_not_winter = data.filter_by_value(
data_dict, 'season', {3})
data_name, data_not_name = data.filter_by_value(data_winter, 'is_holiday',
{1})
dict_list = [data_name, data_not_name]
for m, k in enumerate(title_list):
statistics.population_statistics(k, dict_list[m], 't1', 'cnt', 13.0,
is_above, statistic_functions)
is_above = 1
print("If t1>13.0, then:")
for n, l in enumerate(title_list):
statistics.population_statistics(l, dict_list[n], 't1', 'cnt', 13.0,
is_above, statistic_functions)
def Q2(data):
"""
this func prints the requirements for Q2
:param data: dict
:return: none
"""
winter_time = (dt.filter_by_feature(data, "season", {3}))[0]
yes_holiday, no_holiday = dt.filter_by_feature(winter_time, "is_holiday",
{1})
print_statements = ["If t1<=13.0, then:", "If t1>13.0, then:"]
print("\nQuestion 2:")
for index, elem in enumerate(print_statements):
print(elem)
for key, dict in ({
"Winter holiday records": yes_holiday,
"Winter weekday records": no_holiday
}).items():
stats.population_statistics(key, dict, "t1", "cnt", 13.0, index,
stats.statistic_functions)
def main(argv):
"""
produce answers to Q1, Q2 by user's input
:argument: path to scv file
:parameter: features in csv file for assignment
:return: none
"""
# Q1
print('Question 1:')
features = argv[2].split(
", ") # create a list with continuous variables only
features.remove("season"), features.remove("is_holiday")
stats = [statistics.sum, statistics.mean,
statistics.med] # create a list with statistic functions
data_all = data.load_data(argv[1], argv[2])
data_summer, data_not_summer = data.filter_by_features(
data_all, "season", {1})
print("Summer:")
data.print_details(data_summer, features, stats)
data_holiday, data_not_holiday = data.filter_by_features(
data_all, "is_holiday", {1})
print("Holiday:")
data.print_details(data_holiday, features, stats)
print("All:")
data.print_details(data_all, features, stats)
# Q2
lim_temp = 13
print("\nQuestion 2:")
data_winter, data_not_winter = data.filter_by_features(
data_all, 'season', {3})
data_winter_holiday, data_winter_weekday = data.filter_by_features(
data_winter, 'is_holiday', {1})
features.remove("hum"), features.remove("t1")
stats.remove(statistics.sum)
print("If t1<=13.0, then:") # prints info 13 or under degrees
statistics.population_statistics("winter holiday records",
data_winter_holiday, "t1", "cnt",
lim_temp, 0, stats)
statistics.population_statistics("winter weekday records",
data_winter_weekday, "t1", "cnt",
lim_temp, 0, stats)
print("If t1>13.0, then:") # prints info above 13 degrees
statistics.population_statistics("winter holiday records",
data_winter_holiday, "t1", "cnt",
lim_temp, 1, stats)
statistics.population_statistics("winter weekday records",
data_winter_weekday, "t1", "cnt",
lim_temp, 1, stats)
def main(argv):
"""Main interface for running the program"""
# "london_sample.csv", ['season', 't1', 'is_holiday', 'cnt', 'hum']
# Q1
print(argv)
d = data.load_data(argv[1], argv[2].split(', '))
print("Question 1:")
print("Summer:")
d1, d2 = data.filter_by_feature(d, 'season', [1])
data.print_details(d1, ['hum', 't1', 'cnt'],
[statistics.sum, statistics.mean, statistics.median])
print("Holiday:")
d1, d2 = data.filter_by_feature(d, 'is_holiday', [1])
data.print_details(d1, ['hum', 't1', 'cnt'],
[statistics.sum, statistics.mean, statistics.median])
print("All:")
data.print_details(d, ['hum', 't1', 'cnt'],
[statistics.sum, statistics.mean, statistics.median])
# Q2
print("")
print("Question 2:")
print("If t1<=13.0, then:")
print("Winter holiday records:")
data_main = data.load_data(argv[1], argv[2].split(', '))
data_main_1, data_main_2 = data.filter_by_feature(data_main, 'season', [3])
winter_holiday, is_not_holiday = data.filter_by_feature(
data_main_1, 'is_holiday', [1])
statistics.population_statistics('cnt', winter_holiday, 't1', 'cnt', 13.0,
False,
[statistics.mean, statistics.median])
print("Winter weekday records:")
statistics.population_statistics('cnt', is_not_holiday, 't1', 'cnt', 13.0,
False,
[statistics.mean, statistics.median])
print("If t1>13.0, then:")
print("Winter holiday records:")
statistics.population_statistics('cnt', winter_holiday, 't1', 'cnt', 13.0,
True,
[statistics.mean, statistics.median])
print("Winter weekday records:")
statistics.population_statistics('cnt', is_not_holiday, 't1', 'cnt', 13.0,
True,
[statistics.mean, statistics.median])
def main(argv):
print("Question 1:")
csv_path = argv[1]
features = argv[2]
features = list(features.split(", "))
data = data_lib.load_data(csv_path, features)
statistic_functions = [statistics.sum, statistics.mean, statistics.median]
data1, data2 = data_lib.filter_by_feature(data, "season", [1])
print("Summer:")
data_lib.print_details(data1, ["hum", "t1", "cnt"], statistic_functions)
data1, data2 = data_lib.filter_by_feature(data, "is_holiday", [1])
print("Holiday:")
data_lib.print_details(data1, ["hum", "t1", "cnt"], statistic_functions)
print("All:")
data_lib.print_details(data, ["hum", "t1", "cnt"], statistic_functions)
print("Question 2:")
t_threshold = 13
statistic_func = [statistics.mean, statistics.median]
print("If t1<=13.0, then:")
data1, data2 = data_lib.filter_by_feature(data, "season", [3])
data1, data2 = data_lib.filter_by_feature(data1, "is_holiday", [1])
print("Winter holiday records:")
statistics.population_statistics("Winter holiday records", data1, "t1",
["cnt"], t_threshold, False,
statistic_func)
print("Winter weekday records:")
statistics.population_statistics("Winter weekday records", data2, "t1",
["cnt"], t_threshold, False,
statistic_func)
print("If t1>13.0, then:")
print("Winter holiday records:")
statistics.population_statistics("Winter holiday records", data1, "t1",
["cnt"], t_threshold, True,
statistic_func)
print("Winter weekday records:")
statistics.population_statistics("Winter weekday records", data2, "t1",
["cnt"], t_threshold, True,
statistic_func)
def main(argv):
""" Calculates and prints statistic values for features of records from the data
collected in london.csv file.
:parameter:
argv -- list of arguments supplied (file to run, csv file address, features to get from the csv)
:returns: None
"""
# Question 1
# Saves the features given in a list
features = (argv[2].split(sep=", "))
the_data = data.load_data(argv[1], features)
statistic_functions = [sum, mean, median]
# Saves the relevant records
summer_data, not_summer = data.filter_by_feature(the_data, "season", [1])
holiday_data, not_holiday = data.filter_by_feature(the_data, "is_holiday",
[1])
print("Question 1:")
print("Summer:")
data.print_details(summer_data, ["hum", "t1", "cnt"], statistic_functions)
print("Holiday:")
data.print_details(holiday_data, ["hum", "t1", "cnt"], statistic_functions)
print("All:")
data.print_details(the_data, ["hum", "t1", "cnt"], statistic_functions)
# Question 2
print("\nQuestion 2")
print("If t1<=13.0, then:")
# Saves the relevant records
winter_data, not_winter = data.filter_by_feature(the_data, "season", [3])
w_h_data, not_w_h_data = data.filter_by_feature(winter_data, "is_holiday",
[1])
population_statistics("Winter holiday records:", w_h_data, "t1", ["cnt"],
THRESHOLD, 0, statistic_functions[1:])
population_statistics("Winter weekday records:", not_w_h_data, "t1",
["cnt"], THRESHOLD, 0, statistic_functions[1:])
print("If t1>13.0, then:")
population_statistics("Winter holiday records:", w_h_data, "t1", ["cnt"],
THRESHOLD, 1, statistic_functions[1:])
population_statistics("Winter weekday records:", not_w_h_data, "t1",
["cnt"], THRESHOLD, 1, statistic_functions[1:])
def main(argv):
data = dt.load_data(argv[1], argv[2])
dc = {
"spring": ("season", [0]),
"summer": ("season", [1]),
"autumn": ("season", [2]),
"winter": ("season", [3]),
"holiday": ("is_holiday", [1]),
"weekend": ("is_weekend", [1]),
}
print("Question 1:")
for mode in ["Summer", "Holiday", "All"]:
print(f"{mode}:")
if mode == "All":
dt.print_details(data, ["hum", "t1", "cnt"],
[st.sum, st.mean, st.median])
else:
val = dc[mode.lower()]
dt.print_details(
dt.filter_by_feature(data, val[0], val[1])[0],
["hum", "t1", "cnt"],
[st.sum, st.mean, st.median],
)
print("\nQuestion 2:")
threshold = 13.0
winter_data, _ = dt.filter_by_feature(data, dc["winter"][0],
dc["winter"][1])
holiday_data, weekday_data = dt.filter_by_feature(winter_data,
dc["holiday"][0],
dc["holiday"][1])
print(f"If t1<={threshold}, then:")
print("Winter holiday records:")
st.population_statistics(
"Winter holiday records",
holiday_data,
"t1",
"cnt",
threshold,
False,
[st.mean, st.median],
)
print("Winter weekday records:")
st.population_statistics(
"Winter weekday records",
weekday_data,
"t1",
"cnt",
threshold,
False,
[st.mean, st.median],
)
print(f"If t1>{threshold}, then:")
print("Winter holiday records:")
st.population_statistics(
"Winter holiday records",
holiday_data,
"t1",
"cnt",
threshold,
True,
[st.mean, st.median],
)
print("Winter weekday records:")
st.population_statistics(
"Winter weekday records",
weekday_data,
"t1",
"cnt",
threshold,
True,
[st.mean, st.median],
)