l process a csv file with panda.
My task is to filter the file on the column called `manual_raw_value` as follow 
l want to keep only the rows that satisfy the following condition : 

```
a = ['0','1','2','3','4','5','6','7','8','9',':','/','.',',','%','$','€']

```

keep only the rows where the value of the cell in `manual_raw_value` is only the combination between the char described in `the list a` .

How can l do that ?
l tried the following where l removed the rows where there is alphabet in the cells.

```
 # coding: utf-8

import os
import pandas as pd 
df = pd.read_csv('file.csv',sep=',')
b = ['a','b','c','d','e','f','g','h','i','g','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z','A','B','C','D','E','F','G','H','I','J','K','L','M','N','O','P','Q','R','S','T','U','V','W','X','Y','Z']

joined_2 = "|".join(b)
mask_2 =  ~df['manual_raw_value'].str.contains(joined_2)
cols = ['manual_raw_value']
df = df[mask_2].reset_index(drop=True)
df.to_csv('file_2.csv',index=False,sep=',')

```

What is the efficient way to do that ?