Filter all rows that do not contain letters (alpha) in ´pandas´

Question

I am trying to filter a pandas dataframe using regular expressions. I want to delete those rows that do not contain any letters. For example:

Col A.
50000
$927848
dog
cat 583
rabbit 444

My desired results is:

Col A.
dog
cat 583
rabbit 444

I have been trying to solve this problem unsuccessful with regex and pandas filter options. See blow. I am specifically running into problems when I try to merge two conditions for the filter. How can I achieve this?

Option 1:

df['Col A.'] = ~df['Col A.'].filter(regex='\d+')

Option 2

df['Col A.'] = df['Col A.'].filter(regex=\w+)

Option 3

from string import digits, letters
df['Col A.'] = (df['Col A.'].filter(regex='|'.join(letters)))

OR

df['Col A.'] = ~(df['Col A.'].filter(regex='|'.join(digits)))

OR

df['Col A.'] = df[~(df['Col A.'].filter(regex='|'.join(digits))) & (df['Col A.'].filter(regex='|'.join(letters)))]

Answer 1

I think you'd need str.contains to filter values which contain letters by the means of boolean indexing:

df =  df[df['Col A.'].str.contains('[A-Za-z]')]
print (df)
       Col A.
2         dog
3     cat 583
4  rabbit 444

If there are some NaNs values you can pass a parameter:

df = df[df['Col A.'].str.contains('[A-Za-z]', na=False)]    
print (df)
       Col A.
3         dog
4     cat 583
5  rabbit 444

Answer 2

Have you tried:

df['Col A.'].filter(regex=r'\D')  # Keeps only if there's a non-digit character

or:

df['Col A.'].filter(regex=r'[A-Za-z]')  # Keeps only if there's a letter (alpha)

or:

df['Col A.'].filter(regex=r'[^\W\d_]')  # More info in the link below...

Explanation: https://stackoverflow.com/a/2039476/8933502