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Copy pathutils.py
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124 lines (109 loc) · 3.96 KB
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import webbrowser
from datetime import datetime
from sorcery import dict_of
def get_meta_dict(ratings_data):
this_month_name = datetime.strptime(f"{datetime.today().month}", "%m").strftime(
"%B"
)
this_month = f"{this_month_name},{datetime.today().year}"
this_year = f"{datetime.today().year}"
last_year = f"{int(this_year)-1}"
ratings_data["rated_date_year"] = ratings_data["rated_date"].map(
lambda x: f"{x.year}"
)
ratings_data["rated_date_month"] = ratings_data["rated_date"].map(
lambda x: datetime.strptime(f"{x.month}", "%m").strftime("%B")
)
ratings_data["rated_date_time_day"] = ratings_data["rated_date"].map(
lambda x: "Morning"
if x.hour < 16
else ("Evening" if x.hour >= 16 and x.hour < 20 else "Night")
)
nfilms_month_wise = (
ratings_data["rating"]
.groupby(
ratings_data["rated_date"].map(
lambda x: str(datetime.strptime(f"{x.month}", "%m").strftime("%B"))
+ f",{x.year}"
)
)
.count()
.reset_index()
)
nfilms_this_month = nfilms_month_wise[
nfilms_month_wise["rated_date"] == this_month
]["rating"].values.tolist()
nfilms_this_month = nfilms_this_month[0] if len(nfilms_this_month) > 0 else 0
nfilms_year_wise = (
ratings_data["rating"]
.groupby(ratings_data["rated_date"].map(lambda x: f"{x.year}"))
.count()
.reset_index()
)
nfilms_this_year = nfilms_year_wise[nfilms_year_wise["rated_date"] == this_year][
"rating"
].values.tolist()
nfilms_this_year = nfilms_this_year[0] if len(nfilms_this_year) > 0 else 0
nfilms_most_year, nfilms_most_year_count = nfilms_year_wise.sort_values(
by=["rating"]
).values.tolist()[-1]
last_year_month_stats = (
ratings_data["film_name"][ratings_data["rated_date_year"] == last_year]
.groupby(ratings_data["rated_date_month"])
.count()
.reset_index()
.sort_values(by=["film_name"])
.values.tolist()
)
nfilms_last_year_most_month, nfilms_last_year_most_month_count = (
last_year_month_stats[-1] if len(last_year_month_stats) > 0 else ("None", 0)
)
last_year_month_stats = (
ratings_data["rating"][ratings_data["rated_date_year"] == last_year]
.groupby(ratings_data["rated_date_month"])
.mean()
.reset_index()
.sort_values(by=["rating"])
.values.tolist()
)
nfilms_last_year_most_rated_month, nfilms_last_year_most_rated_month_val = (
last_year_month_stats[-1] if len(last_year_month_stats) > 0 else ("None", 0)
)
nfilms_last_year_most_rated_month_val = round(
nfilms_last_year_most_rated_month_val, 1
)
nfilms_time_of_day = (
ratings_data["film_name"]
.groupby(ratings_data["rated_date_time_day"])
.count()
.reset_index()
.sort_values(by=["film_name"])["rated_date_time_day"]
.values[-1]
)
first_film_name, first_film_rating = ratings_data.sort_values(by=["rated_date"])[
["film_name", "rating"]
].values.tolist()[0]
latest_film_name, latest_film_rating = ratings_data.sort_values(by=["rated_date"])[
["film_name", "rating"]
].values.tolist()[-1]
d = dict_of(
nfilms_this_month,
nfilms_this_year,
nfilms_last_year_most_month,
nfilms_last_year_most_month_count,
nfilms_last_year_most_rated_month,
nfilms_last_year_most_rated_month_val,
nfilms_time_of_day,
first_film_name,
first_film_rating,
latest_film_name,
latest_film_rating,
nfilms_most_year,
nfilms_most_year_count,
)
ratings_data = ratings_data.drop("rated_date_year", axis=1)
ratings_data = ratings_data.drop("rated_date_month", axis=1)
ratings_data = ratings_data.drop("rated_date_time_day", axis=1)
return d
def open_link(url):
webbrowser.open_new_tab(url)