How to Delete Rows from a Pandas DataFrame Based on String Length and Multiple Conditions?

Conditional Row Deletion in Pandas DataFrames

While attempting to remove rows from a DataFrame where a specific column exceeds a given string length, you encountered an error related to "KeyError: u'no item named False'". To resolve this issue, let's explore an alternative approach to conditional row deletion.

Instead of using the expression "len(df['column name']) < 2", you can directly leverage the drop method, which allows you to remove rows based on a specified condition. The drop method takes two arguments:

1. labels: List of labels or indices to remove
2. axis=0: Indicates that rows are being removed

Example:

To remove all rows where the length of the string in the 'name' column is greater than 2:

df = df.drop(df[df['name'].str.len() > 2].index)</p>
<p><strong>In-place Operation:</strong></p>
<p>You can also perform the deletion operation in-place by setting the inplace parameter to True:</p>
<pre class="brush:php;toolbar:false">df.drop(df[df['name'].str.len() > 2].index, inplace=True)

Multiple Conditions:

To apply multiple conditions for row deletion, use the logical operators | (or) and & (and) within parentheses:

df = df.drop(df[(df['age'] < 18) & (df['gender'] == 'male')].index)

This will remove all rows where the age is less than 18 and the gender is 'male'.

The above is the detailed content of How to Delete Rows from a Pandas DataFrame Based on String Length and Multiple Conditions?. For more information, please follow other related articles on the PHP Chinese website!