Ytdyklly

The following script is part of a further education I'm currently enrolled into.

Not all of the code is written by myself. Function signatures for example. Therefore I have put the sections, written by myself, put into # -- Own ---- comment-lines.

Moreover you were given three CSV-files with business data from different cities. The imaginary business was a bikeshare-company.

#!/usr/local/bin/python3

import time

import pandas as pd

import numpy as np

# --- Own Start ----------------------------------------------------------

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

                        'new york city': 'new_york_city.csv',

                        'washington': 'washington.csv' }

feasible_cities     = [ "new york city", "chicago", "washington" ]

feasible_months     = [ "january", "february", "march", "april", "may", "june", "all" ]

feasible_days       = [ "monday", "tuesday", "wednesday", "thursday",

                        "friday", "saturday", "sunday", "all" ]



def ask_user_selection(options, prompt_message):

    answer = ""

    while len(answer) == 0:

        answer = input(prompt_message)

        answer = answer.strip().lower()



        if answer in options:

            return answer

        else:

            answer = ""

            print("Please enter one of the offered options.n")

# -- Own END -----------------------------------------------------------------------------------

def get_filters():

    """

    Asks user to specify a city, month, and day to analyze.



    Returns:

        (str) city - name of the city to analyze

        (str) month - name of the month to filter by, or "all" to apply no month filter

        (str) day - name of the day of week to filter by, or "all" to apply no day filter

    """

    print('n ---- Hello! Let's explore some US bikeshare data! ----n')

    # --- Own Start ----------------------------------------------------------

    # get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs

    city = ask_user_selection(

            feasible_cities,

            "Please enter: 'new york city', 'chicago' or 'washington' > ")



    # get user input for month (all, january, february, ... , june)

    month = ask_user_selection(

        feasible_months, 

        "Please enter month: 'january', 'february', 'march', 'april', 'may', 'june' or 'all' > ")



    # get user input for day of week (all, monday, tuesday, ... sunday)

    day = ask_user_selection(

        feasible_days,

        "Please enter day: 'monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday' or 'all' > ")



    print('-'*40)

    return city, month, day

    # --- Own End ----------------------------------------------------------





def load_data(city, month, day):

    """

    Loads data for the specified city and filters by month and day if applicable.



    Args:

        (str) city - name of the city to analyze

        (str) month - name of the month to filter by, or "all" to apply no month filter

        (str) day - name of the day of week to filter by, or "all" to apply no day filter

    Returns:

        df - Pandas DataFrame containing city data filtered by month and day

    """

    # --- Own Start ----------------------------------------------------------

    df = pd.read_csv(CITY_DATA[city], index_col = 0)



    df['Start Time'] = pd.to_datetime(df['Start Time'])     # Casting "Start Time" to datetime.

    df["month"] = df['Start Time'].dt.month                 # Get the weekday out of the "Start Time" value.

    df["week_day"] = df['Start Time'].dt.weekday_name       # Month-part from "Start Time" value.

    df["start_hour"] = df['Start Time'].dt.hour             # Hour-part from "Start Time" value. 

    df["start_end"] = df['Start Station'].astype(str) + ' to ' + df['End Station']



    if month != 'all':

        month_index = feasible_months.index(month) + 1      # Get the list-index of the month.

        df = df[df["month"] == month_index ]                # Establish a filter for month.



    if day != 'all':

        df = df[df["week_day"] == day.title() ]             # Establish a filter for week day.



    return df

    # --- Own End ----------------------------------------------------------





def time_stats(df):

    """Displays statistics on the most frequent times of travel."""

    # --- Own Start ----------------------------------------------------------

    print('nCalculating The Most Frequent Times of Travel ... n')

    start_time = time.time()



    # display the most common month

    month_index = df["month"].mode()[0] - 1

    most_common_month = feasible_months[month_index].title()



    print("Most common month: ", most_common_month)



    # display the most common day of week

    most_common_day = df["week_day"].mode()[0]

    print("Most common day: ", most_common_day)



    # display the most common start hour

    most_common_hour = df["start_hour"].mode()[0]

    print("Most common hour: ", most_common_hour)



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

    print('-'*40)

    # --- Own End ----------------------------------------------------------





def station_stats(df):

    """Displays statistics on the most popular stations and trip."""

    # --- Own Start ----------------------------------------------------------

    print('nCalculating The Most Popular Stations and Trip ...n')

    start_time = time.time()



    # display most commonly used start station

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

    print("Most used start: ", most_used_start)



    # display most commonly used end station

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

    print("Most used end: ", most_used_end)



    # display most frequent combination of start station and end station trip

    most_common_combination = df["start_end"].mode()[0]

    print("Most common used combination concerning start- and end-station: ", 

            most_common_combination)



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

    print('-'*40)

    # --- Own End ----------------------------------------------------------





def trip_duration_stats(df):

    """Displays statistics on the total and average trip duration."""

    # --- Own Start ----------------------------------------------------------

    print("nCalculating Trip Duration ...n")

    start_time = time.time()



    # display total travel time

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

    print("Total time of travel: ", total_travel_time)



    # display mean travel time

    average_time = df["Trip Duration"].mean()

    print("The average travel-time: ", average_time)



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

    print('-'*40)

    # --- Own End ----------------------------------------------------------





def user_stats(df):

    """Displays statistics on bikeshare users."""

    # --- Own Start ----------------------------------------------------------

    print('nCalculating User Stats ...n')

    start_time = time.time()



    # Display counts of user types

    print("Count of user types: ", 

            df["User Type"].value_counts())



    # Display counts of gender

    if "Gender" in df:

        print("nCounts concerning client`s gender")

        print("Male persons: ", df.query("Gender == 'Male'").Gender.count())

        print("Female persons: ", df.query("Gender == 'Female'").Gender.count())



    # Display earliest, most recent, and most common year of birth

    if "Birth Year" in df:

        print("nEarliest year of birth: ", df["Birth Year"].min())

        print("Most recent year of birth: ", df["Birth Year"].max())

        print("Most common year of birth: ", df["Birth Year"].value_counts().idxmax())



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

    print('-'*40)

    # --- Own End ----------------------------------------------------------





def main():

    while True:

        city, month, day = get_filters()  

        df = load_data(city, month, day)



        time_stats(df)

        station_stats(df)

        trip_duration_stats(df)

        user_stats(df)

        # --- Own Start ----------------------------------------------------------

        restart = input('nWould you like to restart? Enter yes or no.n')

        if restart.lower() != 'yes':

            break

        # --- Own End ----------------------------------------------------------





if __name__ == "__main__":

    main()

Here's a screenshot how it looks on the command line:

The script has passed the review. But nevertheless I would appreciate other opinions.

What have I done well and should keep it up? What could I have done better and why?

The ask_user_selection function could be implemented a bit simpler,
by using a while True: loop, and an early return:

def ask_user_selection(options, prompt_message):

    while True:

        answer = input(prompt_message).strip().lower()



        if answer in options:

            return answer



        print("Please enter one of the offered options.n")