Скачать или смотреть How to Create a TimeStamp Column in a Pandas DataFrame from Separate Date and Time Columns

Learn how to easily combine separate date and time columns into a new `TimeStamp` column in your Pandas DataFrame for effective data manipulation.
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How to Create a TimeStamp Column in a Pandas DataFrame from Separate Date and Time Columns

When working with data in Python, especially with dates and times, you may encounter a common predicament: having your date and time details separated in two different columns. This separation can hinder effective data analysis and manipulation. If you're using Pandas, the good news is that there's a straightforward way to consolidate these columns into a single column formatted as a TimeStamp. Let’s delve into how to achieve this.

The Problem: Separated Date and Time

Consider the following Pandas DataFrame that contains vehicle entry information. It includes num_plate_ID, cam, entry_date, and entry_time:

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

Your goal is to create a new column named entry which combines the entry_date and entry_time into a single TimeStamp format. In the end, you want your DataFrame to look like this:

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

The Solution: Merging Date and Time Columns

To merge the date and time into a new column in your DataFrame, follow these steps outlined in the code snippet below:

Step 1: Import the Required Libraries

Ensure you have imported the Pandas library before starting. If you haven’t done so yet, add this line to your code:

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

Step 2: Create Your DataFrame

First, create the DataFrame from your dictionary of data.

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

Step 3: Combine Date and Time

Next, merge the entry_date and entry_time into a single string representation of the date and time.

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

Step 4: Convert to TimeStamp

Finally, convert the new column entry into datetime format using pd.to_datetime():

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

Result

Your DataFrame now contains the newly formatted TimeStamp column that looks like this:

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

Conclusion

Merging separate date and time columns into a single TimeStamp column in a Pandas DataFrame is a hassle-free process that can greatly enhance the quality of your data analysis. By following the steps outlined above, you can effectively combine and manipulate your date and time data for smoother workflows and improved insights. Give it a try in your next project!