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Learn Challenge: Is this Common Issue? | Working with Dates and Times in pandas
Dealing with Dates and Times in Python

bookChallenge: Is this Common Issue?

In the previous chapter, we found out that issues with negative durations happened because of misusage of 12-h and 24-h formats. We printed the first 10 rows and saw that in all of these rides dropoff_calculated has the same minute and second (accurate to 1 second), but hours differ by 12.

Let's continue our investigation!

Task

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  1. Filter the observations in df dataframe to only with negative duration. Save it in df_neg variable.
  2. Iterate over rows of df_ned. If minute in dropoff_datetime and dropoff_calculated is not the same, you need to print this row.
  3. Within the same for loop count number of rows having an hour in dropoff_datetime greater or equal than 12.

Solution

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SectionΒ 4. ChapterΒ 6
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bookChallenge: Is this Common Issue?

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In the previous chapter, we found out that issues with negative durations happened because of misusage of 12-h and 24-h formats. We printed the first 10 rows and saw that in all of these rides dropoff_calculated has the same minute and second (accurate to 1 second), but hours differ by 12.

Let's continue our investigation!

Task

Swipe to start coding

  1. Filter the observations in df dataframe to only with negative duration. Save it in df_neg variable.
  2. Iterate over rows of df_ned. If minute in dropoff_datetime and dropoff_calculated is not the same, you need to print this row.
  3. Within the same for loop count number of rows having an hour in dropoff_datetime greater or equal than 12.

Solution

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Everything was clear?

How can we improve it?

Thanks for your feedback!

close

Awesome!

Completion rate improved to 3.23
SectionΒ 4. ChapterΒ 6
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