JSON Viewer
View, filter and sort JSON data in seconds.
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View and filter JSON files online
Our JSON viewer allows you to upload and view JSON files directly in your browser. It supports complex data structures and provides a clean interface for easy browsing through key-value pairs.
This tool is optimized for handling large JSON files and offers fast performance, making it ideal for developers and data analysts.
Upload your JSON file and start exploring your data immediately.
View JSON files quickly without any software installation.
Handles JSONL format for professional-level viewing.
Supports large JSON files with smooth performance.
Clean interface for easy browsing through key-value pairs.
Fully browser-based—no installations required.
Perfect for professionals working with JSON data.
JSON format
Java Script Object Notation (JSON) is a format that was designed for use with the Javascript Programming Language.
JSON files do not have a schema or required columns. Each row can have different field names and types. This can
make JSON files difficult to analyze.
How to view and filter JSON files online
- Upload your JSON file
- Your file will be loaded and then you can view your JSON data
- Sort data by clicking a column name
- Filter a column by clicking the three dots
- Export your JSON file in CSV or Excel format by clicking the export button
How to view and filter JSON files in Python with Pandas
First, we need to install pandas
pip install pandas
Then we can load the JSON file into a dataframe.
df = pd.read_json('path/to/file.json')
We can view the first few rows of the dataframe using the head method.
print(df.head(n=5))
The n parameter controls how many rows are returned. Increase it to show more rows.
We can view the last few rows of the dataframe using the tail method.
print(df.tail(n=5))
We can sort the dataframe using the sort_values method.
df = df.sort_values('column_name', ascending=true)
Just replace 'column_name' with the name of the column you want to sort by. The 'ascending' parameter controls whether the values will be sorted in 'ascending' or 'descending' order.
We can filter the dataframe using comparison operators. The following statement will filter a dataframe to rows where the value of the 'column_name' column is greater than 5.
df = df[df['column_name'] > 5]
How to view and filter JSON files in Python with DuckDB
First, we need to install duckdb for Python
pip install duckdb
The following duckdb query will create a view from the input JSON file.
duckdb.sql("""SELECT * from path/to/file.json""")
Sometimes we have large file and it's impractical to read the whole file. We can read the first 5 rows using the following.
duckdb.sql("""SELECT * from path/to/file.json limit 5""")
We can sort rows using the ORDER BY clause and a SQL comparison operator.
duckdb.sql("""SELECT * from path/to/file.json order by 'column_name' ASC limit 5""")
Just change 'column_name' for the column you want to sort by. Use ASC to sort ascending or DESC to sort descending.
We can also filter using SQL comparison operators and the WHERE clause.
duckdb.sql("""SELECT * from path/to/file.json where 'column_name' > 5 ASC limit 5""")
You can change the 'column_name' to change the column you want to filter by. The operator (>) and value (5) control how the filtering is applied to 'column_name'.
MT cars
Motor Trends Car Road Tests dataset.
filename
mtcars.json
rows
32
Flights 1m
1 Million flights including arrival and departure delays.
filename
flights-1m.json
rows
1000000
Iris
Iris plant species data set.
filename
iris.json
rows
50
House price
Housing price dataset.
filename
house-price.json
rows
545
Weather
Weather dataset with temperature, rainfall, sunshine and wind measurements.
filename
weather.json
rows
366