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()