London Bike

#Import pandas,zipfile,& kaggle libraies
import pandas as pd

#Read CSV
bikes = pd.read_csv("london_merged.csv")

#Explore Data
bikes.info()
bikes.shape
bikes

#Unique count on weather_code
bikes.weather_code.value_counts()

#Unique count on season
bikes.season.value_counts()

# Update column names 
new_colums_dict ={
    'timestamp':'time',
    'cnt':'count', 
    't1':'temp_real_C',
    't2':'temp_feels_like_C',
    'hum':'humidity_percent',
    'wind_speed':'wind_speed_kph',
    'weather_code':'weather',
    'is_holiday':'is_holiday',
    'is_weekend':'is_weekend',
    'season':'season'
}

# Renaming the columns to the specified column names
bikes.rename(new_colums_dict, axis=1, inplace=True)

# Change to %
bikes.humidity_percent = bikes.humidity_percent / 100

#Season dictionary int to str
season_dict = {
    '0.0':'Spring',
    '1.0':'Summer',
    '2.0':'Autumn',
    '3.0':'Winter'
}

bikes.season = bikes.season.astype(str)
bikes.season = bikes.season.map(season_dict)

#Weather dictionary int to str
weather_dict = {
    '1.0':'Clear',
    '2.0':'Scattered Clouds',
    '3.0':'Broken Clouds',
    '4.0':'Cloudy',
    '7.0':'Rain',
    '10.0':'Rain with Thunderstorm',
    '26.0':'Snowfall',
}

bikes.weather = bikes.weather.astype(str)
bikes.weather = bikes.weather.map(weather_dict)

#Check dataframe changes
bikes.head()

#Final dataframe to Excel file for Tableau viz
bikes.to_excel('london_bike_final.xlsx', sheet_name='Data')