story_bike_share_analyze_1.py

import datetime as dt
import re

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

from geopy import distance
from pandas.api.types import CategoricalDtype


# Create the day of week Category by iterrating over 7 days (March 4th, 2019 is a Monday)
days = [(dt.datetime(2019, 3, 4) + dt.timedelta(days=x)).strftime('%a') for x in range(0, 7)]
day_type = CategoricalDtype(categories=days, ordered=True)

# Create the month Category by iterrating over the months
months = [dt.datetime(2019, x, 1).strftime('%B') for x in range(1, 13)]
month_type = CategoricalDtype(categories=months, ordered=True)

df = pd.read_csv('./data/bikeshare_ridership.csv')