Reputation:
I have a dataframe with some columns, one of this is Text
that contains some text (obv).
Several cells of this columns have "no text" in there, but I have noticed ( I don't know why) that there are some spaces: for example in some rows I have "no text"
in others " no text"
, " no text "
and " no text "
and so on.
I thought to use a condition like this to remove the rows whose column Text
misses it:
data = data.drop(data['no text' in data['Text']].index)
but gives me some errors (KeyError: '[False] not found in axis'
)
I know that for stuff like this, one have to pass a boolean condition, df = df.drop(df[boolean_cond])
so what am I doing wrong?
Upvotes: 0
Views: 2120
Reputation: 34046
If you want to remove rows which contain string as no text
then you can do this:
data = data[~(data['Text'].str.contains("no text"))]
Upvotes: 3