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Dealing with Dates and Times in Python
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Conteúdo do Curso

Dealing with Dates and Times in Python

Dealing with Dates and Times in Python

1. Working with Dates
What Day is it Today?Creating a Date ObjectDate AttributesDate MethodsDate FormatsOne More FormattingDate DifferenceArithmetic Operations with timedelta Objects
2. Working with Times
What Time is it Now?Creating a datetime ObjectDatetime AttributesDatetime MethodsDatetime Formats12-Hour and 24-Hour FormatsDate and Time DifferenceReading Date and Time from String
3. Timezones and Daylight Savings Time (DST)
The Variery of TimezonesTimezone ExamplesApplying Timezone to Datetime ObjectWhat Time is it in ... ?Daylight Savings Time
4. Working with Dates and Times in pandas
Challenge: What Will We Work With?Challenge: Converting Columns into datetime TypeChallenge: Extreme Trips DurationsChallenge: InvestigationChallenge: Negative Trip DurationChallenge: Is this Common Issue?Challenge: Fixing the IssuesChallenge: Average Metrics Across Taxi TypesChallenge: Corrected Metrics Across Taxi TypesChallenge: Group by Period?

bookChallenge: What Will We Work With?

Welcome to the last section of this course! Now it's time for you to try to implement the acquired knowledge to work with some real-life data. As the first, we will work with taxi rides data in Mexico City.

By this time you should be familiar with the main pandas principles. Let's begin with the exploration of the dataset.

Tarefa

The dataset is loaded in df variable. You need to get the dimensionality (number of rows and columns) and information about columns and their types.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 4. Capítulo 1
toggle bottom row

bookChallenge: What Will We Work With?

Welcome to the last section of this course! Now it's time for you to try to implement the acquired knowledge to work with some real-life data. As the first, we will work with taxi rides data in Mexico City.

By this time you should be familiar with the main pandas principles. Let's begin with the exploration of the dataset.

Tarefa

The dataset is loaded in df variable. You need to get the dimensionality (number of rows and columns) and information about columns and their types.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 4. Capítulo 1
toggle bottom row

bookChallenge: What Will We Work With?

Welcome to the last section of this course! Now it's time for you to try to implement the acquired knowledge to work with some real-life data. As the first, we will work with taxi rides data in Mexico City.

By this time you should be familiar with the main pandas principles. Let's begin with the exploration of the dataset.

Tarefa

The dataset is loaded in df variable. You need to get the dimensionality (number of rows and columns) and information about columns and their types.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Welcome to the last section of this course! Now it's time for you to try to implement the acquired knowledge to work with some real-life data. As the first, we will work with taxi rides data in Mexico City.

By this time you should be familiar with the main pandas principles. Let's begin with the exploration of the dataset.

Tarefa

The dataset is loaded in df variable. You need to get the dimensionality (number of rows and columns) and information about columns and their types.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Seção 4. Capítulo 1
Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
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