json validation code example

Example 1: how to verify json format is valid

I use Gson class in order to convert a
Json object into a java object.
If it works without any error, it means that it is a valid json format...

import com.google.gson.Gson;

public class JSONUtils {

  Gson gson = new Gson();

  public boolean isJSONValid(String jsonInString) {
      try {
          gson.fromJson(jsonInString, Object.class);   
          return true;
      } catch(com.google.gson.JsonSyntaxException e) { 
          return false;
      }
  }
}

Example 2: JSON validate

S=pd.Series(['Finland','Colombia','Florida','Japan','Puerto Rico','Russia','france'])
[itm[0] for itm in S.str.findall('^[Ff].*') if len(itm)>0]

Example 3: JSON validate

**Output:** ['Finland', 'Florida', 'france']

Example 4: JSON validate

#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

Example 5: JSON validate

# Get countries starting with letter P
S=pd.Series(['Finland','Colombia','Florida','Japan','Puerto Rico','Russia','france'])
S[S.str.match(r'(^P.*)')==True]

Example 6: JSON validate

import numpy as np
df['first_five_Letter']=df['Country (region)'].str.extract(r'(^w{5})')
df.head()