//Best tool for JSON Validation
https://jsonlint.com/
import numpy as np
df['first_five_Letter']=df['Country (region)'].str.extract(r'(^w{5})')
df.head()
**Output:** ['Finland', 'Florida', 'france']
if (/^[],:{}s]*$/.test(text.replace(/["/bfnrtu]/g, '@').
replace(/"[^"
]*"|true|false|null|-?d+(?:.d*)?(?:[eE][+-]?d+)?/g, ']').
replace(/(?:^|:|,)(?:s*[)+/g, ''))) {
//the json is ok
}else{
//the json is not ok
}
#convert column to string
df['movie_title'] = df['movie_title'].astype(str)
#but it remove numbers in names of movies too
df['titles'] = df['movie_title'].str.extract('([a-zA-Z ]+)', expand=False).str.strip()
df['titles1'] = df['movie_title'].str.split('(', 1).str[0].str.strip()
df['titles2'] = df['movie_title'].str.replace(r'([^)]*)', '').str.strip()
print df
movie_title titles titles1 titles2
0 Toy Story 2 (1995) Toy Story Toy Story 2 Toy Story 2
1 GoldenEye (1995) GoldenEye GoldenEye GoldenEye
2 Four Rooms (1995) Four Rooms Four Rooms Four Rooms
3 Get Shorty (1995) Get Shorty Get Shorty Get Shorty
4 Copycat (1995) Copycat Copycat Copycat