Sep-05-2019, 12:30 AM
Hi all, first post to the forum!
I'm getting an index error(shown after script) when running the following code, I would be very grateful if someone could explain why.
I'm getting an index error(shown after script) when running the following code, I would be very grateful if someone could explain why.
import time
import pandas as pd
import numpy as np
CITY_DATA = { 'chicago': 'chicago.csv',
'new york city': 'new_york_city.csv',
'washington': 'washington.csv' }
months = ['jan', 'feb', 'mar', 'apr',
'may', 'jun', 'jul',
'aug', 'sep', 'oct', 'nov', 'dec']
days = ['mon', 'tues', 'wed', 'thur', 'fri',
'sat', 'sun']
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('Hello! Let\'s explore some US bikeshare data!')
#Get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs
x = ''
for item in CITY_DATA:
if x == '':
x += item.title()
else:
x += ', ' + item.title()
city = input('Please enter one of the following cities: {}\n'.format(x)).lower()
while city not in CITY_DATA:
city = input('Invalid input. ' +
'please enter one of the following cities:\n{}\n'.format(x)).lower()
#Get user input for month (all, january, february, ... , june)
x = ''
for item in months:
if x == '':
x += item
else:
x += ', ' + item.title()
month = input('Please enter one of the following to filter by month:\n{}\n'.format(x)).lower()
while month not in months and month != 'all':
month = input("\nInvalid selection. " +
"Please enter one of the following options to filter by month. " +
"\n(All, {})\n".format(x)).lower()
#Get user input for day of week (all, monday, tuesday, ... sunday)
x = ''
for item in days:
if x == '':
x += item.title()
else:
x += ', ' + item.title()
day = input('Please enter one of the following to filter by day:\nAll, {}\n'.format(x)).lower()
while day not in days and day != 'all':
day = input("\nInvalid selection. " +
"Please enter one of the following options to filter by day." +
"\n(All, {})\n".format(x)).lower()
print('-'*40)
return city, month, day
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
"""
df = pd.read_csv(CITY_DATA.get(city))
if 'Start Time' in df.columns:
df['Start Time'] = pd.to_datetime(df['Start Time'])
df['month'] = df['Start Time'].dt.month
df['day_of_week'] = df['Start Time'].dt.weekday_name
if month != 'all':
df = df[df['month'] == (months.index(month) + 1) ]
if day != 'all':
df = df[df['day_of_week'] == day.title()]
if 'End Time' in df.columns:
df['End Time'] = pd.to_datetime(df['End Time'])
print('\nFILTER SECTION:\nCity: {}\nMonth: {}\n Day: {}'.format(city, month, day))
return df
def time_stats(df):
"""Displays statistics on the most frequent times of travel."""
print('\nCalculating The Most Frequent Times of Travel...\n')
start_time = time.time()
# TO DO: display the most common month
print('The most common month is: ', months[df['month'].mode()[0] - 1].title())
# TO DO: display the most common day of week
print('The most common day of the week is: ', df['day_of_week'].mode()[0])
# TO DO: display the most common start hour
df['start_hour'] = df['Start Time'].dt.hour
print('Most common start hour: ', df['start_hour'].mode()[0])
print('\n This took %s seconds.' % (time.time() - start_time))
print('-'*40)
def station_stats(df):
"""Displays statistics on the most popular stations and trip."""
print('\nCALCULATING THE MOST POPULAR STATION AND TRIP...\n')
start_time = time.time()
#Display most commonly used start station
df2 = df[df['start_hour'] == df['start_hour'].mode()[0]]
print('The most commonly used start station: ', df2['Start Station'].mode()[0])
#Display most commonly used end station
print('The most commonly used end station: ', df['End Station'].mode()[0])
#Display most frequent combination of start station and end station trip
x = str(df.groupby(['Start Station', 'End Station']).size().sort_values(ascending=False).head(1).index[0])
x = x.replace('(', '').replace(')', '').replace("'", '')
print('Most frequent combination of start and end station: ',x.strip())
print('\n This took %s seconds.' % (time.time() - start_time))
print('-'*40)
def seconds_to_datestamp(seconds):
"""Format seconds to days, hours, minutes, seconds"""
seconds_in_day = 86400
seconds_in_hour = 3600
seconds_in_minuet = 60
day = seconds // seconds_in_day
seconds = seconds - (days * seconds_in_day)
hours = seconds // seconds_in_hour
seconds = seconds - (minuets * seconds_in_hour)
minuets = seconds // seconds_in_minuet
seconds = secinds - (minuets * seconds_in_minuet)
return'{0:.0f} days, {1:.0f} hours, {2:.0f} minuets, {3:0f} seconds'.format(days, hours, minuets, seconds)
def trip_duration_stats(df):
"""Displays statistics on the total and average trip duration."""
print('\nCALCULATING TRIP DURATION...\n')
start_time = time.time()
#Display total travel time
print('Total Travel Time: ', seconds_to_datestamp(df['Trip Duration'].sum()))
#Display mean travel time
print('Mean Travel Time: ', seconds_to_datestamp(df['Trip Duration'].mean()))
print('\nThis took %s seconds.' % (time.time() - start_time))
print('-'*40)
def user_stats(df):
"""Displays statistics on bikeshare users."""
print('CALCULATING USER STATS...\n')
start_time = time.time()
#Display counts of user types
if 'User Type' in df.columns:
x = '\n' + df['User Type'].value_counts().to_string()
else:
x = 'N/A'
print('Count of user types: {}'.format(x))
#Display counts of gender
if 'Gender' in df.columns:
x = '\n' + df['Gender'].value_counts().to_string()
else:
x = 'N/A'
print('\nCount of Genders: {}'.format(x))
#Display earliest, most recent, and most common year of birth
if 'Birth Year' in df.columns:
x = int(df['Birth Year'].min())
else:
x = 'N/A'
print('\nEarliest year of birth: {}'.format(x))
if 'Birth Year' in df.columns:
x = int(df['Birth Year'].max())
else:
x = 'N/A'
print('\n Most recent birth year: {}'.format(x))
if 'Birth Year' in df.columns:
x = int(df['Birth Year'].mode()[0])
else:
x = 'N/A'
print('Most common year of birth: {}'.format(x))
print('\nThis took %s seconds.' % (time.time() - start_time))
print('-'*40)
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)
counter = 1
for i, (index,row) in enumerate(df.iterrows()):
print('\n', row)
if counter%5 == 0:
if input('\nWould you like to view more records? (Yes or No)').lower() == 'no':
break
elif (i == df.shape[0]):
break
counter += 1
restart = input('\nWould you like to restart? (Yes or No)').lower()
if restart.lower() != 'yes':
break
if __name__ == '__main__':
main()Error:Traceback (most recent call last):
File "/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py", line 3118, in get_value
tz=getattr(series.dtype, 'tz', None))
File "pandas/_libs/index.pyx", line 106, in pandas._libs.index.IndexEngine.get_value
File "pandas/_libs/index.pyx", line 114, in pandas._libs.index.IndexEngine.get_value
File "pandas/_libs/index.pyx", line 162, in pandas._libs.index.IndexEngine.get_loc
File "pandas/_libs/hashtable_class_helper.pxi", line 958, in pandas._libs.hashtable.Int64HashTable.get_item
File "pandas/_libs/hashtable_class_helper.pxi", line 964, in pandas._libs.hashtable.Int64HashTable.get_item
KeyError: 0Error:Traceback (most recent call last):
File "bikeshare.py", line 239, in <module>
main()
File "bikeshare.py", line 218, in main
time_stats(df)
File "bikeshare.py", line 105, in time_stats
print('The most common month is: ', months[df['month'].mode()[0] - 1].title())
File "/opt/conda/lib/python3.6/site-packages/pandas/core/series.py", line 767, in __getitem__
result = self.index.get_value(self, key)
File "/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py", line 3124, in get_value
return libindex.get_value_box(s, key)
File "pandas/_libs/index.pyx", line 55, in pandas._libs.index.get_value_box
File "pandas/_libs/index.pyx", line 70, in pandas._libs.index.get_value_box
IndexError: index out of bounds