Python flatten dictionary to dataframe. Returns: A dictionary (or specified mapping type) representation of the DataFrame Examples Example 1: In this example, we convert the DataFrame into a dictionary where each column name maps to a list of How do I convert a list of dictionaries to a pandas DataFrame? The other answers are correct, but not much has been explained in terms of advantages and limitations of these methods. Dec 5, 2018 · Here is my pandas dataframe, and I would like to flatten. flatten(). How do we split or flatten the properties column into multiple columns based on the key values in the map? Jul 27, 2023 · Distinct Flatten dictionaries Using Stack-based iterative function we use a stack-based iterative function to flatten the dictionary. It can also be nested and contains multiple sets as a value for a key. I've tried reading it as a json, changing its type using ast. DataFrame({'date': k, **v} for d in dct for k, v in d. OrderedDict or others if desired. to_json Convert a DataFrame to JSON format. The desired output should resemble a table with the . pd. We construct a dictionary where the values are lists and convert it into a DataFrame. For each iteration, we pop a dictionary from the stack and iterate over its key-value pairs. 2 Currently column "d" of my dataframe contains a list of 14 dictionaries, i want to make it so each value of the dictionary is a seperate column. This method is easy to understand and implement for those new to Python. Whether you are working with data from a complex JSON response, hierarchical data in a database, or multi - dimensional arrays in a scientific 74 pd. from_dict method is then used to convert the dictionary to a Pandas DataFrame. See also DataFrame. The pd. Jul 11, 2025 · into (class, default=dict) is the collection type used for the resulting dictionary. reset_index (level, drop, inplace) Parameters: level - removes only the specified levels from the index drop - resets the index to the default integer Jan 16, 2020 · I converted the dataframe column to dictionary and processed the data there. They are collections of key-value pairs, much like a real-world dictionary where you look up a word (key) to find its meaning (value). DataFrame(sr. flatten() [source] # Flatten list values. from_dict Create a DataFrame from a dictionary. I needed the dictionary to be exploded and then appended to the same row it came from. Using a Queue Using a queue, we enqueue tuples of the current Jul 15, 2025 · Output: Using the Pandas 2. Flattening is defined as Converting or Changing data format to a narrow format. Flattening dictionaries can seem daunting at first, but with the right tools in Python, it becomes a straightforward task that dramatically improves the readability and accessibility of your data. Changed in version 3. T for k, v in user_dict. While dictionaries are incredibly useful data structures, navigating through multiple levels to access the data you need can be cumbersome. Using from_dict () Method The pd. One of the columns contained a list with one dictionary in each list. json_normalize (data, errors='raise', sep='. 7. In Python, it's easy to forget that the keys in a dictionary are ordered. Apr 12, 2024 · The DataFrame. Feb 23, 2024 · Problem Formulation: When working with XML data in Python, it’s often necessary to parse complex nested structures into a tabular DataFrame format for easier analysis and manipulation. Flatten the nested dictionaries: – You can flatten the nested dictionaries by recursively iterating through the dictionary and extracting key-value pairs. mapping. Unlike traditional methods of dealing with JSON data, which often require nested loops or verbose transformations, json_normalize() simplifies the process, making data analysis and manipulation more straightforward. Method 2: Exploding Lists into Rows Pandas allows you to “explode” lists in DataFrame columns, which means transforming Nov 7, 2024 · Learn to flatten YAML files in Python using recursive functions, manual traversal, flatdict, flatten-dict, and Pandas. Flattening the dataframe is one of them. Iterate through each element ele in test_list. d = &quot;&quot;&quot;[ Dec 5, 2024 · Explore various methods to flatten nested dictionaries in Python, keeping the key structure and enhancing usability. Example: invoices = [ { Feb 22, 2024 · This code snippet defines a recursive function flatten_dict() that traverses the nested dictionary and collects key-value pairs into a flat dictionary. Master dictionary to DataFrame conversion for data analysis. g. DataFrame([dict_]) key 1 key 2 key 3 0 value 1 value 2 value 3 EDIT: In the pandas docs one option for Apr 20, 2024 · As a Python developer, you‘ll often encounter deeply nested dictionaries in your data. Jul 23, 2025 · Using reset_index () function Pandas provide a function called reset_index () to flatten the hierarchical index created due to the groupby aggregation function in Python. tolist() and df. With this in mind, it is possible to improve upon the currently accepted answer in terms of simplicity and performance by use a dictionary comprehension to build a dictionary mapping keys to sub-frames. The aim of this post will be to show examples of these methods under different situations, discuss when to use (and when not to use), and suggest alternatives. 7: Dictionary order is guaranteed to be insertion order. Syntax: pandas. You can read more about python dictionaries here. from_dict # classmethod DataFrame. Example: Let consider, the data frame that contains values like payments in four months. from_dict () method provides more flexibility and allows us to specify orientation of DataFrame using the orient parameter. I want to extract that into a pandas dataframe. Mar 8, 2024 · This approach utilizes Python’s list comprehension and dictionary manipulation to flatten each nested dictionary and construct individual DataFrames. Feb 21, 2024 · An effective way to convert a dictionary to a CSV file in Python is by using the pandas. See How to flatten a nested JSON recursively, with flatten_json? for a more thorough explanation if using flatten_json. 01. Oct 25, 2025 · Converting JSON data into a Pandas DataFrame makes it easier to analyze, manipulate, and visualize. to_numpy(). I have a 1mb JSON file of online so Dec 8, 2018 · We have a DataFrame that looks like this: DataFrame[event: string, properties: map<string,string>] Notice that there are two columns: event and properties. This can be done in several ways - one example is shown below - how to get inner values embedded in dictionary lists: data = { 'Java': { 'OOP': ['a', 'v', Oct 21, 2024 · How to flatten this mapping into the expected dataframe below? Follow-up: I eventually want to replace the 'cat_val' with its original categorical values from the mapping enc. The orient argument determines the orientation of the data. Info_column is actually a pandas dataframe column ? Jul 15, 2025 · 0 Since I'm not really sure about what you want your end object to be, and ignoring the Pandas side, I've coded a recursive flattener for the type of dictionary you exhibited. Best way to flatten (strangely) nested JSON / dicts in lists in dicts in a list Hi. For instance a column named person with a row containing a record like {"Name Jan 28, 2021 · Sometimes I have nested object of dictionaries and lists, frequently from a JSON object, that I need to deal with in Python. The advantage of the flattened list is Increases the computing speed and Good understanding of data. We loop until the stack is empty. concat({ Jan 18, 2019 · 13 You should use json_normalize to flatten the dictionary after YAML loads: pd. items()}, axis=0) Or, pd. Jul 15, 2025 · The pd. In most cases, bashing that sort of structure with the following hammer of a snippet works to fully flatten the structure, such that each column’s dictionary keys get horizontally stretched out into new columns. We initialize a stack with the root dictionary and an empty list. tolist() are concise and effective, but I spent a very long time trying to learn how to 'do the work myself' via list comprehension and without resorting built-in functions. Jun 24, 2019 · Spark Python Pyspark How to flatten a column with an array of dictionaries and embedded dictionaries (sparknlp annotator output) Asked 6 years, 3 months ago Modified 6 years, 3 months ago Viewed 5k times Feb 19, 2024 · This code snippet demonstrates how you can create a Pandas DataFrame with lists as column values. It uses pandas' pd. Here is an example of converting a nested dictionary to a 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: >>> dict_ = {'key 1': 'value 1', 'key 2': 'value 2', 'key 3': 'value 3'} >>> pd. I want to convert this DataFrame to a python dictionary. It returns a flat dictionary, whose keys are constructed by concatenating the successive keys for nested dicts, and appending indexes for the successive items of lists: Nov 29, 2024 · In this article, we will explore how to flatten a Pandas DataFrame with JSON columns in Python 3, making it easier to work with and analyze the data. Dec 5, 2024 · This comprehensive guide provides multiple methods for converting a Python dictionary to a DataFrame using Pandas, complete with practical examples and alternative approaches. values. Often I want to load this into a Pandas dataframe, but accessing and mutating dictionary column is a pain, with a whole bunch of expressions like . However, the last column of this dataframe has a dictionary of values ins Jul 23, 2025 · Using reset_index () function Pandas provide a function called reset_index () to flatten the hierarchical index created due to the groupby aggregation function in Python. I tried a few of the other answers for multiple datasets but they're all close but not quite what I want. 7 and turning it into a Pandas DataFrame. literal_eval (), and even trying to break it down further by converting the column into other types. I am querying this data using Python2. Here is a screenshot of the first row of a 16 million-row dataframe: And here is a sample of the Nov 17, 2017 · How to flatten a list of dicts from a Pandas DataFrame into several columns? Asked 7 years, 11 months ago Modified 1 year, 10 months ago Viewed 4k times May 19, 2022 · I would like to flatten a dictionary that is inside the dataframe. These flat dictionaries are then used to construct the DataFrame. Although a nested dictionary helps us store hierarchical data efficiently, we cannot interpret and understand the nested dictionary in its original form. Parameters: datadict Of the form {field : array-like} or {field : dict}. A list is a I often run into cases where a Pandas dataframe contains columns with JSON or dictionary structures. Oct 6, 2016 · It takes a dataframe that may have nested lists and/or dicts in its columns, and recursively explodes/flattens those columns. By using the dictionary's columns or indexes and allowing for Dtype declaration, it builds a DataFrame object. I have generalized it a bit below: def explode_column_from_list_dict(df_in, column_name_to_explode): Aug 25, 2016 · I'm trying to flatten the nested dictionary: dict1 = { 'Bob': { 'shepherd': [4, 6, 3], 'collie': [23, 3, 45], 'poodle': [2, 0, 6], }, 'Sarah': { 'shepherd': [1, 2, 3 I have a DataFrame with four columns. Series. DataFrame. from_dict () The DataFrame. I am trying to convert JSON to CSV file, that I can use for further analysis. Issue with my structure is that I have quite some nested dict/lists when I convert my JSON file. It involves creating columns for each of the 5 values of both the "d" and "p" dicts, as well as appl Mar 31, 2021 · Lets flatten the nested dict into list of records, then create a new dataframe pd. Why Should Yo Apr 28, 2023 · One possible approach to flatten a nested dictionary is to compress its keys. load(f), 'reviews', 'doc') reviewer stars doc 0 Paul 5 Book1 1 Sam 2 Book1 2 John 4 Book2 3 Sam 3 Book2 4 Pete 2 Book2 pandas. Subsequently, these DataFrames are merged into a single DataFrame with pd. It traverses through the nested structure, extracting keys and values at all levels, and then flattens them into a single-level dictionary. The task is to take a dict structure like {'A': [1, 2, 3], 'B': [4, 5, 6]} and turn it into a DataFrame with two columns named ‘A’ and ‘B’, filled with corresponding values. from_dict(data, orient='columns', dtype=None, columns=None) [source] # Construct DataFrame from dict of array-like or dicts. This makes the data multi-level and we need to flatten it as per the project requirements for better readability, as explained below. May 20, 2020 · The input doesn't seem a valid python format. DataFrame. What is flattening dataframe pandas Nov 27, 2024 · Python Dictionaries for Engineers In Python, dictionaries are one of the most powerful and versatile data structures. Pandas provides a built-in function- json_normalize (), which efficiently flattens simple to moderately nested JSON data into a flat tabular format. I'm using my national weather-service api and it returns a list of dictionaries. But how do these options compare on a realistic, larger JSON dataset? Let‘s use a 26 MB dictionary generated from a database of 10,000 users. I tried to use pandas Creating dataframe from dictionary object. concat({k: pd. json_normalize to explode the dictionaries (creating new columns), and pandas' explode to explode the lists (creating new rows). d = &quot;&quot;&quot;[ 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: >>> dict_ = {'key 1': 'value 1', 'key 2': 'value 2', 'key 3': 'value 3'} >>> pd. json. I'm trying to flatten a list of dictionaries with dictionaries in them. If ele is a key in subs_dict, then append A dictionary in python contains one or multiple key-value pair sets of values. Flattening a dictionary, or converting it to a single level, can make your data easier to work with. For this step we are going to create additional DataFrame: Jul 11, 2025 · We are given a list of dictionaries, and the task is to combine all the key-value pairs into a single dictionary. This method helps us convert data into a dictionary-like format and control its structure. Here’s an example: Apr 28, 2021 · I have a Pandas dataframe df that looks as follows: Expenses date manufacturer department 2021. ordinal_encoder. orient{‘columns’, ‘index’, ‘tight Apr 21, 2023 · Time Complexity: O (n*n) where n is the number of elements in the list “test_list”. nesting via columns). DataFrames consist of rows, columns, and data. from_dict(data Jul 27, 2022 · Doesn't seem to want to work as the gitlab ide keeps wanting to recognize the data as a string instead of as a dictionary. DataFrames are 2-dimensional data structures in pandas. Nov 22, 2021 · In this article, we are going to see how to convert nested JSON structures to Pandas DataFrames. May 20, 2025 · Learn powerful methods to convert Python dictionaries to Pandas DataFrames with real-world example. Mar 1, 2019 · I have a particular nested dictionary that I can not figure out how to flatten into a dataframe. Jul 11, 2025 · Output Geeks For geeks 1 dataframe using list 2 10 20 30 Convert List of Dictionaries to a Pandas DataFrame Using pd. For each method I’ll point out the pros and cons, and I'll give a quick performance analysis. I want the elements of first column be keys and the elements of other columns in the same row be values. Jan 21, 2022 · I've come across this problem very often now: I've got a nested dict (typically from an API / JSON payload) and need to flatten in for consumption as tabular data. For this tutorial, I ran all examples on Python 3. This article guides you through five effective methods to transform a complex JSON into an analyzable, flat data structure, suitable for data science or machine learning applications. Jul 30, 2022 · Flattens JSON objects in Python. Structured like this; [ { Mar 11, 2024 · Method 1: Using a Simple For Loop A straightforward approach to flatten a list of dictionaries is by using a simple for loop to iterate over the list and update a new dictionary with the items from each dictionary. import pandas as pd data = {'events': [{'id': 142896214, 'playerId': 37831, 'teamId': 3157, May 1, 2024 · To flatten multiple nested dictionaries into a dataframe, you can follow these general steps: 1. load method is used to load the YAML data from the file into a Python dictionary. concat accepts a dictionary. Indeed, the three rows aren't wrapped in a bigger list or structure. apply(lambda x: x[0]['a']['b']). By default, it is the built-in Python dict, but can be set to collections. Understanding JSON Columns in a Pandas DataFrame JSON (JavaScript Object Notation) is a popular data format used for storing and exchanging data between a server and a web application. Series The data from all lists in the series flattened. How can I do that ? The input I have key column 1 {'health_1': 45, 'health_2': 60, 'health_3': 34, 'health_4': 60, 'name': 'Tom'} 2 {' I have data saved in a postgreSQL database. It’s a clean and simple approach for initializing DataFrame columns with list data. Jan 26, 2025 · In Python, dealing with nested data structures such as nested lists and dictionaries is a common task. from dict () method in Pandas builds DataFrame from a dictionary of the dict or array type. DataFrame(v). Series(object) df = pd. Jul 16, 2015 · I just wanted to note (as this is one of the top results for converting from a nested dictionary to a pandas dataframe) that there are other ways of nesting dictionaries that can be also be converted to a dataframe (e. JSON with multiple levels In this case, the nested JSON data contains another JSON object as the value for some of its attributes. flatten_json flattens the hierarchy in your object which can be useful if you want to force your objects into a table. A nested dictionary can contain several other nested dictionaries inside it. Auxiliary Space: O (n) where n is the number of elements in the list “test_list”. # Converting a nested dictionary to a DataFrame with keys as columns If the keys of the supplied dictionary should be columns of the DataFrame, then set the argument to "columns" (which is the default). This is to be able to plot temperature and other weather data. Creates DataFrame object from dictionary by columns or by index allowing dtype specification. We are using the pandas json_normalize () method and passing nested dictionary and separator values to flatten the dictionary. Jul 27, 2021 · By Miguel Brito In this post, we’ll look at 4 different ways to flatten a dict in Python. Series constructor from the pandas library. Method 1: Recursive Function … So far we have used a small example dictionary to demonstrate flattening functionality. You can also change the shape or dimension of the dataset. Here's a step-by-step guide to achieve this: Mar 3, 2021 · I'm trying to flatten out a nested dictionary into a pandas dataframe. A simple way to handle this is to flatten the objects before I put them into the dataframe Jan 2, 2014 · The previously mentioned df. json_normalize(yaml. Inside pandas, we mostly deal with a dataset in the form of DataFrame. Examples Jun 1, 2021 · 1 I had a data frame that contained several columns. Returns: pandas. Feb 23, 2024 · Imagine receiving a JSON file with multiple levels of hierarchy, and you need to flatten this structure for use within a pandas DataFrame. Jan 29, 2023 · I am trying to convert an object/dictionary to a Python DataFrame using the following code: sr = pd. Method #3: Using a for loop and append method for flattening the dictionary: Step-by-step approach: Create an empty list called res. Below is my data: pandas. Apr 21, 2020 · I am trying to convert a dictionary: data_dict = {'t1': '1', 't2': '2', 't3': '3'} into a dataframe: key | value| ---------------- t1 1 t2 2 t3 3 To do that, I tried Pandas is a python package that allows to creation a dataframe from the dataset. the problem is that it is multiple nested and with inconsistent data For e. In this entire tutorial, you will know how to flatten pandas' dataframe using various methods. May 13, 2019 · I am new to Dask and am looking to find a way to flatten a dictionary column in a PANDAS dataframe. I would appreciate s Feb 25, 2024 · The json_normalize() function in Pandas is a powerful tool for flattening JSON objects into a flat table. io. ', max_level=None) Parameters: data: dict or list of dicts errors: {‘raise Dec 2, 2020 · In this article, we are going to see how to flatten a list of DataFrames. flatten # Series. 03 Mercedes Servic Feb 21, 2024 · Problem Formulation: Often when working with data in Python, we need to transform a dictionary into a pandas DataFrame with dictionary keys as DataFrame columns. Sometimes you will need to access data in flatten format. tolist()) display(df) It works well but some of the o Sep 19, 2023 · Learn, how to flatten a list of pandas dataframe? By Pranit Sharma Last updated : September 19, 2023 Pandas is a special tool that allows us to perform complex manipulations of data effectively and efficiently. If a value is a nested dictionary then it is pushed back onto the stack for further flattening, otherwise the key-value pair is added to the result. Jul 11, 2025 · Explanation: Stack stores tuples of the current dictionary and its parent key; we process each dictionary, concatenating keys and adding key-value pairs to the flattened dictionary. Sep 19, 2019 · I have a csv with 500+ rows where one column "_source" is stored as JSON. Jul 27, 2018 · Dictionary/maps are very common data structures in programming and data worlds. – One common approach is to use a recursive function to traverse the nested dictionaries and flatten them into a single-level dictionary. from_dict() function. Apr 4, 2025 · The Python script is designed to recursively flatten a multi-level nested JSON object or a list of JSON objects into a tabular format (DataFrame). After flattening the dictionary we are converting the data frame to Oct 22, 2012 · I have a dict of lists in python: content = {88962: [80, 130], 87484: [64], 53662: [58,80]} I want to turn it into a list of the unique values [58,64,80,130] I wrote a manual solution, but it's a Feb 9, 2023 · In this example, the yaml. Riccardo's answer mostly worked for me. Oct 7, 2020 · Flatten dictionary to dataframe [duplicate] Asked 4 years, 6 months ago Modified 4 years, 6 months ago Viewed 543 times Jul 25, 2025 · Explore effective Python techniques to transform deeply nested dictionaries into a flat structure, simplifying data processing and access. Nov 27, 2024 · Next let‘s explore 4 ways to implement dictionary flattening in Python. I need each key to be its own column. Syntax pandas. Oct 13, 2018 · An issue with flatten_json is, if there are many positions, then the number of columns for each event in events can be very large. concat. Flattening these structures can simplify data processing, analysis, and make it easier to perform operations that require a single, flat structure. For example, if we have: d = [ {'a': 1}, {'b': 2}, {'c': 3}] then the output will be {'a': 1, 'b': 2, 'c': 3} Using the update () method In this method we process each dictionary in the list one by one and add its key-value pairs to a single dictionary using update () method hence May 25, 2022 · Also, the order of the keys in the dictionary matters: the fields of the struct are created in the same order as the keys in the dictionary. list. import pandas as pd data = [{'name': 'vikash', 'age': 27}, {'name': 'Satyam', 'age': 14}] df = pd. This method involves creating a pandas DataFrame object from the dictionary, and then using the to_csv() method of the DataFrame to export it to CSV format. from_dict () method constructs a DataFrame from a dictionary. Actually, the data is stored in a list format. DataFrame constructor and pd. Once you have created the dataframe then you can manipulate this dataset easily. So i'd have 60 columns total. Note Mar 28, 2024 · Using the from_dict Method The code creates a Pandas DataFrame (df) from a nested dictionary (data) with a 3-level MultiIndex by flattening the dictionary and setting the DataFrame's index accordingly. Jul 12, 2025 · Approach 2: Using flatten_json library The json-flatten library provides functions for flattening a JSON object to a single key-value pairs, and unflattening that dictionary back to a JSON object. items()) To flatten a dictionary of lists into a pandas DataFrame in Python, you can use the pd. In this guide, we‘ll explore four different ways to flatten a Aug 19, 2020 · I have a JSON which I converted into a dictionary and trying to make a dataframe out of it. Then converted the processed dictionary to dataframe and joined with original dataframe by 'index'. sw8 prsvo v42c ljg jqgv umluo8c bw4xx jgds gxriqk arim