Pandas Read JSON

Reading JSON Data

JSON (JavaScript Object Notation) stores data as nested key-value pairs, structurally very close to a Python dictionary. The pd.read_json() function accepts a file path, a URL, or a JSON string, and converts it straight into a DataFrame.

import pandas as pd

df = pd.read_json('data.json')
print(df.to_string())

Reading JSON From a Python Dictionary

If your JSON-like data is already loaded in memory as a Python dictionary, you do not need read_json() at all - pd.DataFrame() converts it directly, since a dictionary of dictionaries maps naturally onto rows and columns.

import pandas as pd

data = {
    "Duration": {"0": 60, "1": 60, "2": 60},
    "Pulse": {"0": 110, "1": 117, "2": 103},
    "Calories": {"0": 409, "1": 479, "2": 340}
}
df = pd.DataFrame(data)
print(df)

• Accepts a file path, a URL, or a raw JSON string
• orient controls how pandas interprets the JSON structure
• lines=True reads newline-delimited JSON (JSON Lines) files
• convert_dates automatically parses date-like columns

Reading JSON Lines Format

Some systems export JSON as one record per line rather than a single array - this format is known as JSON Lines. Set lines=True so pandas parses each line as its own record instead of expecting one big JSON document.

import pandas as pd

df = pd.read_json('records.jsonl', lines=True)
print(df.head())