Скачать или смотреть How to Compare and Subtract Dates in Pandas DataFrames

Discover effective methods to compare and subtract dates in a Pandas DataFrame. Learn how to identify if dates fall within a specified range with this comprehensive guide.
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Comparing and Subtracting Dates in Pandas DataFrames

Working with time-related data can be tricky, especially when you want to analyze dates from a DataFrame. A common requirement in data analysis is to compare dates to see if they fall within a certain range. In this post, we will tackle the problem of determining if dates in a column fall within 7 days of another date in the same column.

The Problem

Imagine you have a DataFrame containing favorite dates of individuals along with their names and companies. Here’s a simplified view of how the data looks:

firstnamelastnamecompanyfavedayRickSmithCFA2020-03-16JohnJonesWND2020-04-30DavidWilsonINO2020-01-10............You want to check, in the current sorted order of the DataFrame, whether a date is within 7 days of another date in the same group of individuals.

The Objective

You would like to add a new column seven_days that indicates whether each date is within 7 days of another date in the same group. For example, rows belonging to David Wilson with dates 2020-01-10 and 2020-01-13 should yield TRUE, while 2020-01-31 should yield FALSE.

The Solution

To achieve this, we can use a combination of Pandas’ groupby functionality and a custom function that evaluates the date differences. Here’s a step-by-step breakdown of the solution:

1. Setting Up the DataFrame

Ensure that you have the required libraries installed. We’ll be using pandas and numpy:

[[See Video to Reveal this Text or Code Snippet]]

2. Define the Custom Function

We will define a custom function to evaluate if a date is within the 7-day limit:

[[See Video to Reveal this Text or Code Snippet]]

3. Grouping and Transforming Data

Now we group the DataFrame by first name, last name, and company, and apply our custom function:

[[See Video to Reveal this Text or Code Snippet]]

4. Output the Results

Finally, let's take a look at the modified DataFrame with the new column:

[[See Video to Reveal this Text or Code Snippet]]

Expected Output

Your DataFrame should now look similar to:

firstnamelastnamecompanyfavedayseven_daysDavidWilsonINO2020-01-10TRUEDavidWilsonINO2020-01-13TRUEDavidWilsonINO2020-01-31FALSEJimMillerMCD2020-10-13TRUEJimMillerMCD2020-10-20TRUEJimMillerMCD2020-10-28FALSEJohnJonesWND2020-04-30TRUERickSmithCFA2020-03-11TRUERickSmithCFA2020-03-16TRUEConclusion

In this guide, we tackled the task of checking whether dates within a group in a Pandas DataFrame fall within 7 days of each other. By utilizing the powerful combination of groupby and custom functions, we efficiently achieved our goal. Now you can apply this method to your datasets and enhance your data analysis capabilities!

If you found this guide helpful or have any questions about working with dates in Pandas, feel free to leave a comment!