Use word count in Pandas dataframe to drop rows with only one word

Question

I have a dataframe (data) with 2 records: ``` id text 0001 The farmer plants grain 0002 tuna ``` I want to count the number of words in the `text` column of this dataframe and drop rows with only one word. I know how to count the number of words: ``` count = data['text'].str.split().str.len() ``` How do I use the results to run an IF statement that will drop rows in the dataframe? Any IF statements such as... ``` if count == 1: print('drop') ``` ...results in this error: ``` Traceback (most recent call last): File "", line 32, in if count == 1: File "C:\Users aca\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas\core\generic.py", line 917, in __nonzero__ .format(self.__class__.__name__)) ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all(). ``` I have read the Pandas documentation and other SO questions around this error, but I can't seem to get the solutions to apply correctly to m…

Accepted Answer

use a mask:

```
dropped = data[~(count==1)].copy()
```

explanation:

so assuming a df such has:

```
data = pd.DataFrame({'text': ['hello my name is','hey']})
```

using your count method you could check if it =1 or not, creating a boolean mask :

```
count = data['text'].str.split().str.len()
~(count==1)
Out[18]: 
0     True
1    False
Name: text, dtype: bool
```

now you can apply that mask :

```
data[~(count==1)]
Out[22]: 
               text
0  hello my name is
```

Use word count in Pandas dataframe to drop rows with only one word

Solution

Problem