JSON Viewer

View, filter and sort JSON data in seconds.

View and filter JSON data instantly
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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

  1. Upload your JSON file
  2. Your file will be loaded and then you can view your JSON data
  3. Sort data by clicking a column name
  4. Filter a column by clicking the three dots
  5. 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'.

CSV viewer

View and filter CSV files

Parquet viewer

View and filter Parquet files

TSV viewer

View and filter TSV files

JSON viewer

View and filter JSON files

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