Conteúdo do Curso

Dealing with Dates and Times in Python

1. Working with Dates

What Day is it Today?Creating a Date Object Date Attributes Date Methods Date Formats One More Formatting Date Difference Arithmetic Operations with timedelta Objects

2. Working with Times

What Time is it Now?Creating a datetime Object Datetime Attributes Datetime Methods Datetime Formats 12-Hour and 24-Hour Formats Date and Time Difference Reading Date and Time from String

3. Timezones and Daylight Savings Time (DST)

The Variery of Timezones Timezone Examples Applying Timezone to Datetime Object What 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 Type Challenge: Extreme Trips Durations Challenge: Investigation Challenge: Negative Trip Duration Challenge: Is this Common Issue?Challenge: Fixing the Issues Challenge: Average Metrics Across Taxi Types Challenge: Corrected Metrics Across Taxi Types Challenge: Group by Period?

Challenge: Fixing the Issues

Well, in the last chapter you saw, that there were only two rides with negative durations where minutes in both columns were different. But if paid your attention to seconds, you might notice, that that were the minute ending and starting (59 seconds, and 00 respectively). It means that all the inconsistencies can be interpreted as misuages of 12 and 24-hour formats.

Since we have investigated the real reason for the issue, we can now fix it! Let me remind you of one of the ways to replace values in dataframe based on some condition - .where function.


              1
            
df['col_name'].where(~(condition), inplace = True, other = values_to_replace)

Using the following approach all the values in col_name will be replaced with values_to_replace if (condition) is True.

Tarefa

For all the trips with negative duration add 12 hours to dropoff_datetime column.
Calculate column duration again.
Print first 5 rows of updated df.

Tarefa

For all the trips with negative duration add 12 hours to dropoff_datetime column.
Calculate column duration again.
Print first 5 rows of updated df.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Seção 4. Capítulo 7

Challenge: Fixing the Issues

Since we have investigated the real reason for the issue, we can now fix it! Let me remind you of one of the ways to replace values in dataframe based on some condition - .where function.


              1
            
df['col_name'].where(~(condition), inplace = True, other = values_to_replace)

Using the following approach all the values in col_name will be replaced with values_to_replace if (condition) is True.

Tarefa

For all the trips with negative duration add 12 hours to dropoff_datetime column.
Calculate column duration again.
Print first 5 rows of updated df.

Tarefa

For all the trips with negative duration add 12 hours to dropoff_datetime column.
Calculate column duration again.
Print first 5 rows of updated df.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Seção 4. Capítulo 7

Challenge: Fixing the Issues

Since we have investigated the real reason for the issue, we can now fix it! Let me remind you of one of the ways to replace values in dataframe based on some condition - .where function.


              1
            
df['col_name'].where(~(condition), inplace = True, other = values_to_replace)

Using the following approach all the values in col_name will be replaced with values_to_replace if (condition) is True.

Tarefa

For all the trips with negative duration add 12 hours to dropoff_datetime column.
Calculate column duration again.
Print first 5 rows of updated df.

Tarefa

For all the trips with negative duration add 12 hours to dropoff_datetime column.
Calculate column duration again.
Print first 5 rows of updated df.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Since we have investigated the real reason for the issue, we can now fix it! Let me remind you of one of the ways to replace values in dataframe based on some condition - .where function.


              1
            
df['col_name'].where(~(condition), inplace = True, other = values_to_replace)

Using the following approach all the values in col_name will be replaced with values_to_replace if (condition) is True.

Tarefa

For all the trips with negative duration add 12 hours to dropoff_datetime column.
Calculate column duration again.
Print first 5 rows of updated df.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Seção 4. Capítulo 7

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo