Nested dictionary json to dataframe. Jun 3, 2022 · Now, I can try pandas again.

Nested dictionary json to dataframe json () converts response to a Python dictionary/list. This guide will walk you through the process step-by-step, from understanding nested JSON to handling edge cases, with practical examples and best practices. This guide provides a complete solution for complex data transformations. May 25, 2022 · each field has a datatype the order of the fields in a struct matters Polars: Mapping Dictionaries to Structs When dictionaries are mapped to structs (e. JSON(JavaScript Object Notation) data and dictionaries can be stored and imported in different ways. Method 1: Using the json. Syntax pandas. I want to flatten my whole data so the final table should look like this. The input is a nested dictionary with potential multiple levels of keys, where each lowest-level key corresponds to a value. Jan 23, 2019 · I prefer to write a function that accepts your mylist and converts it 1 nested layer down and returns a dictionary. I know I could construct the series after iterating over the dictionary entries, but if there is a more direct way this would be very useful. Nov 13, 2025 · If you’ve ever tried to load a nested JSON file into a Pandas DataFrame and ended up with messy columns full of dictionaries or lists, this guide is for you. It uses pandas' pd. DataFrame, but if the dictionaries are nested, the dictionaries are treated as elements. Parameters: datadict Of the form {field : array-like} or {field : dict}. Feb 22, 2024 · Method 1: Using pandas. response. DataFrame. ', max_level=None) Parameters: data: dict or list of dicts errors: {‘raise Feb 23, 2024 · Here we loop over the list of JSON objects, manually unpack and combine nested structures under ‘details’, convert lists to comma-separated strings, and append each flattened dictionary to a list. load() and pd. The desired output is Apr 30, 2025 · Note in this example each json list in the original dataframe is the same, but of course the idea here is to explode each json to its neighbouring new columns, and they could be different of course. The orient='index' parameter tells pandas to use dictionary keys as row labels. In conclusion, reading a JSON file with nested objects into a pandas DataFrame in Python 3 is a straightforward process Feb 16, 2024 · This code demonstrates the creation of a DataFrame by parsing a simple JSON string. JSON with multiple levels In this case, the nested JSON data contains another JSON object as the value for some of its attributes. load() function to parse our JSON data. This conversion enables more sophisticated data manipulation and analysis. Nov 22, 2021 · In this article, we are going to see how to convert nested JSON structures to Pandas DataFrames. A strong, robust alternative to the methods outlined above is the json_normalize function which works with lists of dictionaries (records), and in addition can also handle nested dictionaries. Note, that I no longer have a JSON string but a normal Python list, containing dictionaries. Common issues include nested structures, missing keys, invalid syntax, or mismatched data types. json_normalize to explode the dictionaries (creating new columns), and pandas' explode to explode the lists (creating new rows). The function . In Python's Pandas library, we can utilize the groupby function along with apply to create groupings based on chosen columns. Given a DataFrame in pandas, the Python data analysis library, one might need to export it as a nested JSON object for web applications, APIs, or other purposes where JSON is the preferred format. A similar question would be asking whether it is possible to construct a pandas Jun 19, 2023 · As a data scientist or software engineer working with data, you might come across situations where you need to convert JSON data to a Pandas DataFrame. Unfortunately, there’s no one-size-fits-all solution when it comes to nested Jul 14, 2022 · This article explains how you can create an Apache Spark DataFrame from a variable containing a JSON string or a Python dictionary. This method helps us convert data into a dictionary-like format and control its structure. This process often entails using the json_normalize() function in Pandas to flatten nested dictionaries or lists within the JSON object and create a DataFrame with appropriate columns. Method 3: Using Recursion for Deeply Nested Structures Recursion provides a methodical way to handle deeply nested JSON objects by Jul 23, 2025 · When working with data, it's common to encounter JSON (JavaScript Object Notation) files, which are widely used for storing and exchanging data. Nov 24, 2021 · Need help on the below nested dictionary and I want to convert this to a pandas Data Frame My JSON have the following instance of CPU data and comes with random occurrence: Instance1 [{'datapoints' Mar 5, 2024 · Problem Formulation: When working with data in Python, developers often encounter the need to convert nested dictionaries into a structured MultiIndex DataFrame using Pandas. Jul 30, 2022 · In this article, we will see how to convert JSON or string representation of dictionaries in Pandas. Pandas, a powerful data manipulation library in Python, provides a convenient way to convert JSON data into a Pandas data frame. This article demonstrates several ways to achieve this, with an example DataFrame containing user Sep 9, 2014 · 4 I get JSON data from an API service, and I would like to use a DataFrame to then output the data into CSV. We then create a DataFrame from the list for analysis. In the below example it reads and prints JSON data from the specified API endpoint using the pandas library in Python. You can access individual values, change them, add new rows, delete old ones, merge multiple dictionaries, iterate over them, and even convert the entire thing to a Pandas DataFrame or JSON file. DataFrame. DataFrame(users_summary) The items in "level 1" (the UserId's) are taken as columns, which is the opposite of what I want to achieve (have UserId's as index). We’ll break down the most common techniques to flatten nested JSON structures, with step-by-step examples, code snippets, and solutions to common challenges. get (url) fetches data from the URL. Pandas provides a built-in function- json_normalize (), which efficiently flattens simple to moderately nested JSON data into a flat tabular format. Nov 6, 2024 · Explore effective methods to create a Pandas DataFrame from a nested dictionary structure in Python, along with practical examples and explanations. This might result in unexpected results or need to convert them to new columns. Jul 23, 2025 · A nested JSON example In the above example, the key field " article " has a value which is another JSON format. Feb 8, 2022 · Turning Nested JSON data into dataframes Situation: You’ve connected to an API endpoint, that is structured as a nested json, here’s how to loop through and select certain values into a dataframe for further processing. json_normalize is to build your own dataframe by extracting only the selected keys and values from the nested dictionary. Jul 20, 2021 · I'm trying to create a pandas dataframe form json file. We can convert list of nested dictionary into Pandas DataFrame. Nov 8, 2022 · # Extract relevant data from each line in the JSON structure and create a nested list, # Where the "inner" lists are lists with dicts # (1 line of JSON in my file = 1 inner list, so if my JSON file has 6 # lines the nested list will have 6 lists with a number of dictionaries) data = [json. load () method to load json file into a list and then used the json_normalize on this. Subsequently, we access specific values within the JSON structure using dictionary keys, demonstrating how to retrieve information such as the name, age, city and zipcode. Feb 2, 2024 · 1. json_normalize() Pandas offers a convenient function pandas. Convert Nested List of Dictionary into Pandas Dataframe Below are the methods that will be used Using from_dict (orient Aug 20, 2025 · You want to transform this DataFrameinto a nested dictionary that looks like thisThis is often useful when you need to quickly look up data based on the values in the 'I' column Nov 18, 2018 · but one column has a nested dictionary in a list and therefore the features column contains the column with the list of dictionaries. JSON supports multiple nests to create complex JSON files if required. read_json() is a function to convert JSON strings or files to pandas. 4 days ago · In data analysis, it’s common to encounter nested data structures, especially when working with JSON, API responses, or scraped data. Jul 11, 2025 · Given a list of the nested dictionary, write a Python program to create a Pandas dataframe using it. Let's understand the stepwise procedure to create a Pandas Dataframe using the list of nested dictionary. Method 4: Using json_normalize () The json_normalize() function in Pandas can be employed Feb 8, 2024 · Converting a Pandas DataFrame to a nested dictionary involves organizing the data in a hierarchical structure based on specific columns. Aug 26, 2024 · As we can see, the nested objects “address” and “friends” are expanded into separate columns, with their respective keys as column names. A frequent scenario is a Pandas DataFrame where one column contains **lists of dictionaries**. Method 2: Using json_normalize() To convert a nested JSON object into a flat table, pandas provides the json_normalize() function. Jul 23, 2025 · Using the JSON module In this example, we use the json module to parse a nested JSON string. loads(line)["d"]["results"] for line in f] Nov 13, 2025 · Mapping nested JSON to a Pandas DataFrame requires flattening the hierarchical structure into a flat table. orient{‘columns’, ‘index’, ‘tight Oct 6, 2016 · It takes a dataframe that may have nested lists and/or dicts in its columns, and recursively explodes/flattens those columns. The to_dict() method with `orient=’index’` argument turns the multi-index DataFrame into a nested dictionary. from_dict(nested_data, orient='index') print(df_nested) This technique is particularly useful when working with JSON data, which often comes in nested structures. Jul 11, 2025 · Read the JSON File directly from Web Data You can fetch JSON data from online sources using the requests library and then convert it to a DataFrame. The main reason for doing this is because json_normalize gets slow for very large json file (and might not always produce the output you want). I've seen a multiple solutions to this problem which uses built in functions from_dict/json_normalize yet I'm unable to apply it to my code. May 19, 2025 · } df_nested = pd. json_normalize (data, errors='raise', sep='. Pandas DataFrame to JSON. This will convert it into a Python dictionary, and we can then create the DataFrame directly from the resulting Python data structure. This enables easier manipulation, analysis, and Oct 25, 2025 · Converting JSON data into a Pandas DataFrame makes it easier to analyze, manipulate, and visualize. May 10, 2020 · The Problem APIs and document databases sometimes return nested JSON objects and you’re trying to promote some of those nested keys into column headers but loading the data into pandas gives you Dec 6, 2024 · How can I efficiently read and manipulate nested JSON data using Pandas? Navigating through complex nested JSON structures can be challenging, especially when trying to convert them into a format that is more workable for data analysis, such as a Pandas DataFrame. Learn how to convert a Python dictionary into a Pandas DataFrame effortlessly. , in a DataFrame constructor), each key in the dictionary is mapped to a field name in the struct and the corresponding dictionary value is assigned to the value of that field in the struct. There can be many reasons as to why we need to perform this conversion. from_dict # classmethod DataFrame. In this article, we will discuss the process of converting JSON data to a Pandas DataFrame using Python's Pandas library. Feb 27, 2025 · The `json_normalize` function and the `explode` method in Pandas can be used to transform deeply nested JSON data from APIs into a Pandas DataFrame. Nested JSON to CSV conversion Our job is to convert the JSON file to a CSV format. Learn how to efficiently convert a Pandas DataFrame into a nested JSON structure using Python. So, instead of using the read_json, I used the json. from_dict Create a DataFrame from a dictionary. Updating DataFrames: Strategies and Best Practices Updating existing DataFrames with new data is a common task in data analysis. read_json ()`) to read JSON files directly into DataFrames, JSON’s flexibility can lead to parsing errors. Mar 16, 2023 · pandas. The `pd. This function is specifically designed to handle nested JSON data, but it works equally well with Python dictionaries. g. 000 dictionaries with about 100 key value pairs, nested up to 4 levels deep, into a Pandas DataFrame. Jul 23, 2025 · Parsing Json Nested Dictionary Using Pandas Library In this example, below code uses the `pandas` library to parse JSON data into a DataFrame (`parsed_data`) and then extracts and prints the value associated with the 'city' key within the 'address' column. from_dict(data, orient='columns', dtype=None, columns=None) [source] # Construct DataFrame from dict of array-like or dicts. Therefore, JSON parsing simply means taking the raw JSON data and transforming it into an easy-to-read Feb 18, 2024 · This snippet sets up a multi-index based on ‘Category’ and ‘Item’ columns. Oct 3, 2020 · I'm trying to convert a dataframe that has inside other dataframe like: { 'id': 3241234, 'data': { 'name':'carol', 'lastname': 'netflik', 'office': { Jun 3, 2022 · Now, I can try pandas again. requests. to_json () doesn't give me enough flexibility for my aim. In order to convert See also DataFrame. Simplify the process of working with complex data structures and achieve a specific format for your data analysis tasks. Apr 12, 2024 · A step-by-step illustrated guide on how to convert a nested dictionary to a Pandas DataFrame in multiple ways. Therefore, I can directly use pandas DataFrame class: Jan 14, 2014 · What I am trying to do is extract elevation data from a google maps API along a path specified by latitude and longitude coordinates as follows: from urllib2 import Request, urlopen import json p Jul 15, 2025 · The pd. Method 2: Pandas json_normalize Pandas provides a function called json_normalize that can handle the conversion of nested dictionary structures into pandas. Feb 19, 2024 · This code sends a GET request to the specified URL, parses the JSON response into a Python dictionary, and finally converts that dictionary into a pandas DataFrame. I am using the following code, but it is painfully slow: Dec 12, 2023 · Learn to transform Pandas DataFrames into nested JSON with practical examples, showing various methods for complex data structuring in Python. The following JSON structure serves as an example: df = pandas. json_normalize . 3 Selecting only those columns of interest In case we just want to transform some specific fields into a tabular pandas DataFrame, the json_normalize () command does not allow us to choose what fields to transform. Apr 5, 2019 · And, it takes a list or a dictionary as an input. json_normalize ()` function helps to flatten nested JSON structures into a tabular format. from_dict () method provides more flexibility and allows us to specify orientation of DataFrame using the orient parameter. Nov 8, 2016 · I am trying to convert a Pandas Dataframe to a nested JSON. to_json Convert a DataFrame to JSON format. Jun 19, 2023 · This blog will show you how to efficiently convert nested JSON files into a Pandas DataFrame, a vital skill for data scientists and software engineers. Here, the tuples become the keys of the outer dictionary, and the ‘Value’ becomes the inner dictionary. Here are some data points of the dataframe (in csv, comma separate Method 1: Using the json. Explore different methods with step-by-step examples, handling nested dictionaries, and best practices for data conversion in Pandas. This makes the data multi-level and we need to flatten it as per the project requirements for better readability, as explained below. 406 When converting a dictionary into a pandas dataframe where you want the keys to be the columns of said dataframe and the values to be the row values, you can do simply put brackets around the dictionary like this: Nov 13, 2025 · While Pandas provides a convenient function (`pandas. May 3, 2023 · Despite the dictionary-like layout of the JSON file, it is not human-ready for consumption. The values of these columns are either scalar values or lists of dictionaries, depending on the structure of the nested objects. Therefore, a small preprocessing of the JSON should be performed where we filter just those columns of interest. So, I am trying to convert a list of dictionaries, with about 100. CSV are easy to read when opened in a spreadsheet GUI Mar 8, 2021 · 3 I'm looking for a clean, fast way to expand a pandas dataframe column which contains a json object (essentially a dict of nested dicts), so I could have one column for each element in the json column in json normalized form; however, this needs to retain all of the original dataframe columns as well. Jun 15, 2024 · Each line in the JSONL file may represent a complex JSON object with nested dictionaries or lists, which need to be properly handled during the parsing and transformation into a tabular DataFrame format. This has the added advantage of not requiring you to 'manually' know what key like b to convert. The result is a DataFrame where each dictionary becomes a row, and nested dictionaries remain nested within cells. Apr 18, 2023 · Summing up Nested Dictionary Python There’s a lot that goes into working with nested dictionaries in Python. Jul 23, 2025 · Using json_normalize Normalizing a nested JSON object into a Pandas DataFrame involves converting the hierarchical structure of the JSON into a tabular format. json_normalize() that can be used to flatten nested dictionaries and turn them into a DataFrame. Creates DataFrame object from dictionary by columns or by index allowing dtype specification. Mar 8, 2024 · This code snippet uses the DataFrame constructor from the Pandas library to convert a list of nested dictionaries into a DataFrame. A possible alternative to pandas. DataFrame() functions The easiest and most straightforward approach is to use the built-in json. In this article, we'll explore how to convert JSON data into a Pandas DataFrame, covering various scenarios and options Jul 22, 2020 · Would you please add more detail for priceData? Is it always list with 1 element? How about the json? Is it always list with 1 element? Feb 18, 2024 · Problem Formulation: Converting data structures between formats is a common task in data science. Jul 23, 2025 · Pandas Dataframe To Nested Json in Python Below are some of the ways in which we can convert Pandas DataFrames into Nested JSON in Python: Use to_json () method The most straightforward approach is to use the `to_json` method of pandas, specifying the orientation as 'records'. lefvfj npjvdi yomsuc jsiq rjz zkzfytp dzlke air vzpxnt tlpnk isb axcvz xuv glub mxdnf