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How to print a Pandas DataFrame without the index and with custom column formatting?

Nov 06, 2024 am 06:02 AM

How to print a Pandas DataFrame without the index and with custom column formatting?

Pandas Dataframe: Printing Without Index

When working with Pandas dataframes, it may be desirable to exclude the index when printing the dataframe. Additionally, it may be necessary to modify the formatting of specific columns, such as converting datetime objects to display only the time portion.

To exclude the index when printing a dataframe, use the index parameter within the to_string method. Setting index=False will remove the index from the printed output.

<code class="python">df.to_string(index=False)</code>
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For example, consider the following dataframe:

   User ID           Enter Time   Activity Number
0      123  2014-07-08 00:09:00              1411
1      123  2014-07-08 00:18:00               893
2      123  2014-07-08 00:49:00              1041
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Using the to_string method with index=False will produce the following output:

User ID   Enter Time   Activity Number
123         00:09:00              1411
123         00:18:00               893
123         00:49:00              1041
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To modify the formatting of a specific column, use the strftime method. This method can be used to convert datetime objects to display only the time portion. For example, to display only the time portion of the Enter Time column, use the following code:

<code class="python">df['Enter Time'] = df['Enter Time'].dt.strftime('%H:%M:%S')</code>
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This will modify the Enter Time column to display only the time, without the date.

Combining these techniques, you can print a dataframe without the index and with specific column formatting. For instance, to print the dataframe with only the time portion of the Enter Time column and without the index, use the following code:

<code class="python">print(df[['User ID', 'Enter Time', 'Activity Number']].to_string(index=False))</code>
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This will produce the following output:

User ID   Enter Time   Activity Number
123         00:09:00              1411
123         00:18:00               893
123         00:49:00              1041
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