View by_tepmerature_by_category.py
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from itertools import count, takewhile | |
def frange(start, stop, step): | |
return takewhile(lambda x: x < stop, count(start, step)) | |
def show_avg_hist(df, column, buckets=40): | |
counts = df[column].value_counts() | |
counts = counts[counts > 20] # Drop rare values |
View by_temp.py
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from itertools import count, takewhile | |
def frange(start, stop, step): | |
return takewhile(lambda x: x < stop, count(start, step)) | |
def show_avg_hist(df, column, buckets=40): | |
counts = df[column].value_counts() | |
counts = counts[counts > 20] # Drop rare values |
View by_weekday.py
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from pandas import read_csv | |
crimes_df = read_csv("CrimeData.csv") | |
crimes_df = crimes_df[crimes_df.year <= "2019"] | |
days_df = read_csv("DaysData.csv") | |
from datetime import datetime | |
def to_weekday(date): | |
return datetime.strptime(date, "%m/%d/%Y").strftime("%A") |
View crimes_by_month.py
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def add_day_month_year(df): | |
dates = df["Date"].map(lambda x: x[:10]) | |
df["day_of_month"] = dates.map(lambda x: x.split("/")[1]) | |
df["month"] = dates.map(lambda x: x.split("/")[0]) | |
df["year"] = dates.map(lambda x: x.split("/")[2]) | |
df["date"] = dates | |
return df | |
from pandas import read_csv |
View crimes_by_month.py
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def add_day_month_year(df): | |
dates = df["Date"].map(lambda x: x[:10]) | |
df["day_of_month"] = dates.map(lambda x: x.split("/")[1]) | |
df["month"] = dates.map(lambda x: x.split("/")[0]) | |
df["year"] = dates.map(lambda x: x.split("/")[2]) | |
df["date"] = dates | |
return df | |
from pandas import read_csv |
View by_year_by_type.py
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def add_day_month_year(df): | |
dates = df["Date"].map(lambda x: x[:10]) | |
df["day_of_month"] = dates.map(lambda x: x.split("/")[1]) | |
df["month"] = dates.map(lambda x: x.split("/")[0]) | |
df["year"] = dates.map(lambda x: x.split("/")[2]) | |
df["date"] = dates | |
return df | |
from pandas import read_csv |
View by_month_by_category.py
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def add_day_month_year(df): | |
dates = df["Date"].map(lambda x: x[:10]) | |
df["day_of_month"] = dates.map(lambda x: x.split("/")[1]) | |
df["month"] = dates.map(lambda x: x.split("/")[0]) | |
df["year"] = dates.map(lambda x: x.split("/")[2]) | |
df["date"] = dates | |
return df | |
from pandas import read_csv |
View by_year.py
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def add_day_month_year(df): | |
dates = df["Date"].map(lambda x: x[:10]) | |
df["day_of_month"] = dates.map(lambda x: x.split("/")[1]) | |
df["month"] = dates.map(lambda x: x.split("/")[0]) | |
df["year"] = dates.map(lambda x: x.split("/")[2]) | |
df["date"] = dates | |
return df | |
from pandas import read_csv |
View by_year_by_category.py
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def add_day_month_year(df): | |
dates = df["Date"].map(lambda x: x[:10]) | |
df["day_of_month"] = dates.map(lambda x: x.split("/")[1]) | |
df["month"] = dates.map(lambda x: x.split("/")[0]) | |
df["year"] = dates.map(lambda x: x.split("/")[2]) | |
df["date"] = dates | |
return df | |
from pandas import read_csv |
View by_year.py
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def add_day_month_year(df): | |
dates = df["Date"].map(lambda x: x[:10]) | |
df["day_of_month"] = dates.map(lambda x: x.split("/")[1]) | |
df["month"] = dates.map(lambda x: x.split("/")[0]) | |
df["year"] = dates.map(lambda x: x.split("/")[2]) | |
df["date"] = dates | |
return df | |
from pandas import read_csv |
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