I have a pandas DataFrame and I want to delete rows from it where the length of the string in a particular column is greater than 2.

I expect to be able to do this (per this answer):

df[(len(df['column name']) < 2)]

but I just get the error:

KeyError: u'no item named False'

What am I doing wrong?

(Note: I know I can use df.dropna() to get rid of rows that contain any NaN, but I didn't see how to remove rows based on a conditional expression.)

To directly answer this question's original title "How to delete rows from a pandas DataFrame based on a conditional expression" (which I understand is not necessarily the OP's problem but could help other users coming across this question) one way to do this is to use the drop method:

df = df.drop(some labels)
df = df.drop(df[<some boolean condition>].index)

Example

To remove all rows where column 'score' is < 50:

df = df.drop(df[df.score < 50].index)

In place version (as pointed out in comments)

df.drop(df[df.score < 50].index, inplace=True)

Multiple conditions

(see Boolean Indexing)

The operators are: | for or, & for and, and ~ for not. These must be grouped by using parentheses.

To remove all rows where column 'score' is < 50 and > 20

df = df.drop(df[(df.score < 50) & (df.score > 20)].index)