Dealing with Dates and Times in Python

Challenge: Negative Trip Duration

Well, in the last chapter you might notice that for the first 10 rows all the trips started before 13 hours (1 p.m.), and ended close to 00 hours. What if it's just AM/PM missing? Let's try to check it.

How can it be checked? Well, in our dataframe we also have trip_duration column representing the trip duration in seconds. What if we just add this duration to pickup_datetime and compare it with dropoff_datetime?

Please note, that you will need to use timedelta objects in this task since you want to 'shift' your datetime object for a certain time. To convert column to timedelta type use pd.to_timedelta() function with two arguments: column you want to convert, and unit - dimension used ('S' for seconds, 'm' for minutes, and so on).

Compito

Swipe to start coding

Convert trip_duration column into timedelta type. Do not forget that trip_duration measures in seconds.
Create new column dropoff_calculated as the result of adding pickup_datetime and trip_duration.
Print first 10 rows for updated dataframe.

Please, do not change column names in square brackets.

Soluzione

# Load libraries

import pandas as pd

from datetime import timedelta

# Loading dataset and creating duration column

url = 'https://drive.google.com/uc?id=1KoZJyLO791MqW-JICYukrApH4qfiniGG'

df = pd.read_csv(url, parse_dates = ['pickup_datetime', 'dropoff_datetime'])

df["duration"] = pd.to_timedelta(df["duration"])

# Task 1 - convert trip duration into timedelta type

df["trip_duration"] = pd.to_timedelta(df["trip_duration"], unit = "S")

# Task 2 - create new_column dropoff_calculated

df["dropoff_calculated"] = df["pickup_datetime"] + df["trip_duration"]

# Task 3 - print first 10 rows with negative durations

print(df[df["duration"] < timedelta(0)][["pickup_datetime", "dropoff_datetime", "dropoff_calculated"]].head(10))

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Sezione 4. Capitolo 5

single

# Load libraries

import pandas as pd

from datetime import timedelta

# Loading dataset and creating duration column

url = 'https://drive.google.com/uc?id=1KoZJyLO791MqW-JICYukrApH4qfiniGG'

df = pd.read_csv(url, parse_dates = ['pickup_datetime', 'dropoff_datetime'])

df["duration"] = pd.to_timedelta(df["duration"])

# Task 1 - convert trip duration into timedelta type

df["trip_duration"] = pd.___(df["___"], unit = "___")

# Task 2 - create new_column dropoff_calculated

df["dropoff_calculated"] = df["___"] ___ df["___"]

# Task 3 - print first 10 rows with negative durations

print(df[df["duration"] < ___(___)][["pickup_datetime", "dropoff_datetime", "dropoff_calculated"]].___(___))

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