From your code, it looks like you're loading a JSON file which has JSON data on each separate line. read_json supports a lines argument for data like this:
data_df = pd.read_json('C:/Users/Alberto/nutrients.json', lines=True)
Answer from coldspeed95 on Stack OverflowNote
Removelines=Trueif you have a single JSON object instead of individual JSON objects on each line.
Pandas
pandas.pydata.org › docs › reference › api › pandas.read_json.html
pandas.read_json — pandas 3.0.1 documentation - PyData |
Convert a JSON string to pandas object. This method reads JSON files or JSON-like data and converts them into pandas objects. It supports a variety of input formats, including line-delimited JSON, compressed files, and various data representations (table, records, index-based, etc.).
W3Schools
w3schools.com › python › pandas › pandas_json.asp
Pandas Read JSON
JSON is plain text, but has the format of an object, and is well known in the world of programming, including Pandas. In our examples we will be using a JSON file called 'data.json'. Open data.json. ... Tip: use to_string() to print the entire DataFrame. ... JSON objects have the same format as Python dictionaries.
Videos
How to read a JSON column in Pandas?
If you have a column in a DataFrame containing JSON-like data, use pd.json_normalize() to expand it:
import pandas as pd df = pd.DataFrame({'col': ['{"name": "John", "age": 30}', '{"name": "Jane", "age": 25}']}) df['col'] = df['col'].apply(pd.json_normalize)
This will convert the JSON strings in the column into structured data.
import pandas as pd df = pd.DataFrame({'col': ['{"name": "John", "age": 30}', '{"name": "Jane", "age": 25}']}) df['col'] = df['col'].apply(pd.json_normalize)
This will convert the JSON strings in the column into structured data.
hevodata.com
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A Simplified Guide to Pandas Load JSON: 3 Essential Steps
How to load JSON string into Pandas DataFrame?
To load a JSON string into a Pandas DataFrame, use the pd.read_json() method with the json.loads() from Python’s built-in library:
import pandas as pd import json json_string = '{"name": "John", "age": 30}' df = pd.read_json(json.loads(json_string))
import pandas as pd import json json_string = '{"name": "John", "age": 30}' df = pd.read_json(json.loads(json_string))
hevodata.com
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A Simplified Guide to Pandas Load JSON: 3 Essential Steps
How to load JSON file with Pandas?
You can load a JSON file using Pandas' read_json() method:
import pandas as pd df = pd.read_json('file.json')
This reads the JSON file into a Pandas DataFrame.
import pandas as pd df = pd.read_json('file.json')
This reads the JSON file into a Pandas DataFrame.
hevodata.com
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A Simplified Guide to Pandas Load JSON: 3 Essential Steps
Top answer 1 of 6
56
From your code, it looks like you're loading a JSON file which has JSON data on each separate line. read_json supports a lines argument for data like this:
data_df = pd.read_json('C:/Users/Alberto/nutrients.json', lines=True)
Note
Removelines=Trueif you have a single JSON object instead of individual JSON objects on each line.
2 of 6
14
Using the json module you can parse the json into a python object, then create a dataframe from that:
import json
import pandas as pd
with open('C:/Users/Alberto/nutrients.json', 'r') as f:
data = json.load(f)
df = pd.DataFrame(data)
Pandas
pandas.pydata.org › docs › dev › reference › api › pandas.read_json.html
pandas.read_json — pandas 3.0.0rc1+28.g37421be5bc documentation
Convert a JSON string to pandas object. This method reads JSON files or JSON-like data and converts them into pandas objects. It supports a variety of input formats, including line-delimited JSON, compressed files, and various data representations (table, records, index-based, etc.).
GeeksforGeeks
geeksforgeeks.org › python › how-to-read-json-files-with-pandas
How to Read JSON Files with Pandas? - GeeksforGeeks
July 23, 2025 - DSA Python · Data Science · NumPy · Pandas · Practice · Django · Flask · Last Updated : 23 Jul, 2025 · JSON (JavaScript Object Notation) store data using key-value pairs. Reading JSON files using Pandas is simple and helpful when you're working with data in .json format.
Spark By {Examples}
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Pandas Read JSON File with Examples - Spark By {Examples}
January 10, 2025 - Pandas read_json() function can be used to read JSON file or string into DataFrame. It supports JSON in several formats by using orient param. JSON is
Pandas
pandas.pydata.org › pandas-docs › version › 1.1.3 › reference › api › pandas.read_json.html
pandas.read_json — pandas 1.1.3 documentation
Read the file as a json object per line.
Top answer 1 of 14
324
I found a quick and easy solution to what I wanted using json_normalize() included in pandas 1.01.
from urllib2 import Request, urlopen
import json
import pandas as pd
path1 = '42.974049,-81.205203|42.974298,-81.195755'
request=Request('http://maps.googleapis.com/maps/api/elevation/json?locations='+path1+'&sensor=false')
response = urlopen(request)
elevations = response.read()
data = json.loads(elevations)
df = pd.json_normalize(data['results'])
This gives a nice flattened dataframe with the json data that I got from the Google Maps API.
2 of 14
50
Check this snip out.
# reading the JSON data using json.load()
file = 'data.json'
with open(file) as train_file:
dict_train = json.load(train_file)
# converting json dataset from dictionary to dataframe
train = pd.DataFrame.from_dict(dict_train, orient='index')
train.reset_index(level=0, inplace=True)
Hope it helps :)
Pandas
pandas.pydata.org › pandas-docs › version › 0.25.0 › reference › api › pandas.read_json.html
pandas.read_json — pandas 0.25.0 documentation
>>> df.to_json(orient='records') '[{"col 1":"a","col 2":"b"},{"col 1":"c","col 2":"d"}]' >>> pd.read_json(_, orient='records') col 1 col 2 0 a b 1 c d ... >>> df.to_json(orient='table') '{"schema": {"fields": [{"name": "index", "type": "string"}, {"name": "col 1", "type": "string"}, {"name": "col 2", "type": "string"}], "primaryKey": "index", "pandas_version": "0.20.0"}, "data": [{"index": "row 1", "col 1": "a", "col 2": "b"}, {"index": "row 2", "col 1": "c", "col 2": "d"}]}'
Hevo
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A Simplified Guide to Pandas Load JSON: 3 Essential Steps
January 9, 2026 - Step 3: Load the JSON file in Pandas using the command below. import pandas as pd # you have to showcase the path to the file in your local drive. data = pd.read_json (‘pathfile_name.json') # print the loaded JSON into dataframe print(data)
Python Basics
pythonbasics.org › pandas-json
JSON with Python Pandas - Python Tutorial
Read json string files in pandas read_json(). You can do this for URLS, files, compressed files and anything that’s in json format. In this post, you will learn how to do that with Python.
Stack Abuse
stackabuse.com › reading-and-writing-json-files-in-python-with-pandas
Reading and Writing JSON Files in Python with Pandas
September 7, 2023 - In this article, we've covered how to read and write JSON files using Python's popular Pandas library - from local to remote files.
Medium
medium.com › @amit25173 › what-is-pandas-read-json-and-why-use-it-8ee69f5bfc96
What is pandas.read_json() and Why Use It? | by Amit Yadav | Medium
March 6, 2025 - That’s exactly what pandas.read_json() does—it helps you convert messy JSON data into a structured format called a DataFrame in Python.
Scaler
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How to Load and Manipulate JSON Files with Pandas - Scaler Topics
May 4, 2023 - We can use the read_json() function of the JSON module to read the data using the Pandas module. ... Refer to the next section for more details about the read_json() function. We can also read the JSON data using the JSON module in Python.
pandas
pandas.pydata.org › pandas-docs › dev › reference › api › pandas.read_json.html
pandas.read_json — pandas 3.0.0rc0+6.gfa1360d41a documentation
Convert a JSON string to pandas object. This method reads JSON files or JSON-like data and converts them into pandas objects. It supports a variety of input formats, including line-delimited JSON, compressed files, and various data representations (table, records, index-based, etc.).
GeeksforGeeks
geeksforgeeks.org › python › pandas-parsing-json-dataset
Pandas - Parsing JSON Dataset - GeeksforGeeks
July 11, 2025 - Before working with JSON data we need to import pandas. If you're fetching JSON from a web URL or API you'll also need requests. ... To read a JSON file or URL in pandas we use the read_json function.
datagy
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Pandas read_json - Reading JSON Files Into DataFrames • datagy
February 24, 2023 - The 'columns' orientation provides a format that is like a Python dictionary, where the columns are the keys. The values are also dictionaries, where the keys are the index and the values are the values. Let’s see how you can read this data format: # Read a JSON String Into a Pandas DataFrame Using Columns Orientation import pandas as pd json_string = """{ "Name":{ "0":"Nik", "1":"Kate", "2":"Isla" }, "Age":{ "0":33.0, "1":"None", "2":37.0 }, "Sales":{ "0":33.33, "1":56.32, "2":43.44444 } }""" df = pd.read_json(json_string) print(df) # Returns: # Name Age Sales # 0 Nik 33 33.33000 # 1 Kate 33 56.32000 # 2 Isla 37 43.44444
Pandas
pandas.pydata.org › pandas-docs › version › 1.0.2 › reference › api › pandas.read_json.html
pandas.read_json — pandas 1.0.2 documentation
Read the file as a json object per line.
Apache
spark.apache.org › docs › latest › api › python › reference › pyspark.pandas › api › pyspark.pandas.read_json.html
pyspark.pandas.read_json — PySpark 4.1.1 documentation
>>> df.to_json(path=r'%s/read_json/foo.json' % path, num_files=1) >>> ps.read_json( ... path=r'%s/read_json/foo.json' % path ...
Pandas
pandas.pydata.org › pandas-docs › version › 1.0 › reference › api › pandas.read_json.html
pandas.read_json — pandas 1.0.5 documentation
Read the file as a json object per line.