import pandas as pd

import numpy as np

import time

data_ = { 'chicago': 'chicago.csv',

'newyork': 'new_york_city.csv',

'washington': 'washington.csv' }

def pull_month():

month_option=['January','February','March','April','May','June','July','August','September','October','November','December']

while True:

month = input('Which month you wanna want')

month = month.lower()

if(month in month_option):

break

return month

def pull_day():

days_option=['Sunday','Monday','Tuesday','Wednesday','Thursday','Friday','Saturday']

while True:

day = input('Which day you wanna want?')

day =d ay.lower()

if(day in days_option):

break

return day

def pull_filter():

print('Can we start searching the bike share data')

city_option=['Chicago','Newyork','Washington']

while True:

city = input('Choose One from the options visible Chicago, Newyork, Washington')

city = city.lower()

if(city in city_option):

break

while True:

filter_option = [1,2,3,4]

filter = input('Would you like to filter using month:1 day:2 both:3 nothing:4 enter 1, 2, 3, or 4 ')

filter = int(filter)

if(filter in filter_option):

break

if(filter == 1):

month=pull_month()

day='all'

elif(filter == 2):

day=pull_day()

month='all'

elif(filter == 3):

month=pull_month()

day=pull_day()

elif(filter == 4):

day='all'

month='all'

print('-'*40)

return city, month, day

def load_data(city, month, day):

df = pd.read_csv(data_[city])

df['Start Time'] = pd.to_datetime(df['Start Time'])

df['month'] = df['Start Time'].dt.month

df['day'] = df['Start Time'].dt.weekday_name

if month != 'all':

months = ['January', 'February', 'March', 'April', 'May', 'June','July','August','September','October','November','December']

month = months.index(month)+1

df = df[df['month'] == month]

if day != 'all':

df = df[df['day'] == day.title()]

return df

def common_month(df):

df['month'] = df['Start Time'].dt.month_name()

popular_month=df['month'].mode()[0]

print('Popular Start Month:',popular_month)

def common_day(df):

df['day'] = df['Start Time'].dt.day_name()

popular_day=df['day'].mode()[0]

print('Popular Day:',popular_day)

def common_start_hour(df):

df['hour'] = df['Start Time'].dt.hour

popular_hour=df['hour'].mode()[0]

print('Popular Start Hour:',popular_hour)

def time_stats(df, month, day):

print('Most Frequent Times of Travel')

start_time = time.time()

if(month=='all' and day=='all'):

common_month(df)

common_day(df)

common_start_hour(df)

elif(month!='all' and day == 'all'):

common_day(df)

common_start_hour(df)

elif(month=='all' and day!='all'):

common_start_hour(df)

common_month(df)

elif(month!='all' and day!='all'):

common_start_hour(df)

print("\nThis took %s seconds." % (time.time() - start_time))

print('-'*40)

def station_stats(df):

print('Most Popular Stations and Trip')

start_time = time.time()

popular_start_station=df['Start Station'].mode()[0]

print('Popular Start Station:', popular_start_station)

popular_end_station=df['End Station'].mode()[0]

print('Popular End Station:',popular_end_station)

df['Start End'] = df['Start Station'].map(str) + '&' + df['End Station']

popular_start_end = df['Start End'].value_counts().idxmax()

print('Most Popular frequent combination of start station and end station is',popular_start_end)

print("\nThis took %s seconds." % (time.time() - start_time))

print('-'*40)

def trip_duration_stats(df):

print('\nCalculating Trip Duration...\n')

start_time = time.time()

total_travel_time=df['Trip Duration'].sum()

print('Total Travel Time:',total_travel_time)

mean_travel_time=df['Trip Duration'].mean()

print('Mean Travel Time:',mean_travel_time)

print("This took %s seconds." % (time.time() - start_time))

print('-'*40)

def user_stats(df,city):

print('Calculating User Stats')

start_time = time.time()

user_types = df['User Type'].value_counts()

print('User Type',user_types)

if city=='newyork' or city=='chicago':

gender_types = df['Gender'].value_counts()

print('Gender Type:',gender_types)

earliest_year_birth = int(df['Birth Year'].min())

print('Earliest Year Birth: ',earliest_year_birth)

most_recent_year_birth =int(df['Birth Year'].max())

print('Most Recent Year Birth: ',most_recent_year_birth)

most_common_year_birth = int(df['Birth Year'].mode()[0])

print('Most common Year Birth: ',most_common_year_birth)

print(" %s seconds" % (time.time() - start_time))

print('-'*40)

def main():

while True:

city, month, day = pull_filter()

load_data(city, month, day)

df = load_data(city, month, day)

time_stats(df, month, day)

station_stats(df)

trip_duration_stats(df)

user_stats(df,city)

flag=1

start=0

end=5

while(flag ==1):

flag=int(input("Individual trip data? Type 1 or 2 True:1 False:2'))

while((flag != 1) and (flag!=2)):

flag=int(input('\nPlease enter available input: '))

print(df.iloc[start:end])

start+=5

end+=5

restart = input('do u wanna do again Enter yes or no')

restart = restart.lower()

while((restart != 'yes') and (restart !='no')):

restart=input('input: ')

if restart == 'no':

break

elif restart =='yes':

continue

if __name__ == "__main__":

main()