Is there any legal recourse against unauthorized usage of a private repeater in the USA? I used pprint() to understand the format of the response. Find centralized, trusted content and collaborate around the technologies you use most. How do I check whether a file exists without exceptions? Create a JSON file. I want to convert this csv to a dataframe in python. 505), Convert list of dicts of dict into DataFrame, Generate DF from attributes of tags in list. ; Here is the implementation on Jupyter Notebook please read the inline comments to understand each step. It can be in three formats, 1. How to iterate over rows in a DataFrame in Pandas. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. Asking for help, clarification, or responding to other answers. Can someone guide me on how to perform this please. JSON to parquet ( Conversion ) - Let's break this into steps. 505). Code Review Stack Exchange is a question and answer site for peer programmer code reviews. Use json.dumps to convert the Python dictionary into a JSON string. I am not sure what the usual placeholder value is for missing string values in Python. 0. Note: NaN's and None will be converted to null and datetime objects will be converted to UNIX timestamps. Full list of contributing python-bloggers, Copyright 2022 | MH Corporate basic by MH Themes, Convert JSON to Pandas DataFrame in Python, Scaling Shiny Apps for Python and R: Sticky Sessions on Heroku. The response variable in the below code, stores the returned values, and the JSON output is parsed using the json ( ) method. First, start with a known data source (the URL of the JSON API) and get the data with urllib3. responsedata = responsedata.text jsondata = json.loads (responsedata) datarALL = datarALL + jsondata ["results"] It seems like what you're doing here is to incrementally build a list. Thanks. low, How to iterate over rows in a DataFrame in Pandas. There are 2 inputs you might have and you can also convert between them. Get a list from Pandas DataFrame column headers. Let's take a look at the data types with df.info (). Check it please, How to convert JSON (from python requests) to a pandas dataframe, Speeding software innovation with low-code/no-code tools, Tips and tricks for succeeding as a developer emigrating to Japan (Ep. Does no correlation but dependence imply a symmetry in the joint variable space? and construct the dataframe using data = response.json () df = pd.DataFrame ( [course_dict (item) for item in data]) Keeping related data together makes the code easier to follow. How to transform a js table-data into a .csv table? When the migration is complete, you will access your Teams at stackoverflowteams.com, and they will no longer appear in the left sidebar on stackoverflow.com. In this article we will discuss how to convert JSON to Pandas DataFrame in Python. Keeping related data together makes the code easier to follow. https://jsonblob.com/707ead1c-9891-11e8-b651-496f6b276e89, https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_json.html#pandas.read_json, Speeding software innovation with low-code/no-code tools, Tips and tricks for succeeding as a developer emigrating to Japan (Ep. 1. To learn more, see our tips on writing great answers. Learning to sing a song: sheet music vs. by ear. The only thing I'll say is that, if each publication on Code Review had a presentation as clear, complete and pleasant as yours, the overall quality of this site would be improved. See the following example to know how to use it. It connects to API gets results page by page and combine them together into a list. requests.models.Response. Gate resistor necessary and value calculation, Sci-fi youth novel with a young female protagonist who is watching over the development of another planet. Thanks for contributing an answer to Stack Overflow! Why do my countertops need to be "kosher"? https://jsonblob.com/707ead1c-9891-11e8-b651-496f6b276e89. How do I select rows from a DataFrame based on column values? I generate a dataframe by joining the lists in a dictionary and then converting with pandas. How do I execute a program or call a system command? Below is the code for importing the api extraction in csv format. This is the only thing that interests me. Example for the dump: It only takes a minute to sign up. You can download the example JSON from here. Import the json module in the program. And yes, I made an assumption, that the first value would suffice, for the other line you pointed out about dictionaries. Not the answer you're looking for? By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Which one of these transformer RMS equations is correct? Does Python have a ternary conditional operator? open, Pandas DataFrame has a method dataframe.to_json () which converts a DataFrame to a JSON string or store it as an external JSON file. All formats are covered below: Under what conditions would a society be able to remain undetected in our current world? Find centralized, trusted content and collaborate around the technologies you use most. To read a JSON file via Pandas, we can use the read_json () method. Would drinking normal saline help with hydration? (i) read_json () The read_json () function converts JSON string to pandas object. Browse other questions tagged, Start here for a quick overview of the site, Detailed answers to any questions you might have, Discuss the workings and policies of this site, Learn more about Stack Overflow the company. Add the JSON content to a list. close, The result is a Pandas DataFrame that is human readable and ready for analysis. I can't seems to make this conversion works. Method 1: Using read_json () We can read JSON files using pandas.read_json. Stack Overflow for Teams is moving to its own domain! First, let's create a JSON file that you wanted to convert to a CSV file. If you want to try it out: I would also be careful with what you have because those dictionaries that you are converting might have more than one value, in which case you would miss them. Another Pandas function to convert JSON to a DataFrame is read_json () for simpler JSON strings. Can we prosecute a person who confesses but there is no hard evidence? To learn more, see our tips on writing great answers. salmanwahed 8920 Credit To: stackoverflow.com Stack Overflow for Teams is moving to its own domain! +. Not the answer you're looking for? get each of your lists then create a dataframe, I edited my answer with specifications for your json. Find centralized, trusted content and collaborate around the technologies you use most. read_json () has many parameters, among which orient specifies the format of the JSON string. Print the key: value pairs inside the Python dictionary using a for loop. Python3 Start a research project with a student in my class. Example JSON dictionary within response. This API is mainly designed to convert semi-structured JSON data into a flat table or DataFrame. Making statements based on opinion; back them up with references or personal experience. If I drop out mid-semester, what is the likelihood that I'll have to pay it back? Chain Puzzle: Video Games #02 - Fish Is You, input: listOfDictionaries --> use @VikashSingh solution, input: jsonStr --> use @JustinMalinchak solution. I am not sure what the usual placeholder value is for missing string values in Python. Check the data type and confirm that it is of dictionary type. To learn more, see our tips on writing great answers. https://codepen.io/luis-valencia/pen/pobZqVJ, Now I need to convert this to a pandas dataframe, but I don't know how, specially because in the pandas dataframe I require only", { The easiest way is to just use pd.DataFrame.from_dict method. rev2022.11.15.43034. @Lukas Mller, try below way to create dataframes for data.json import json import requests r = requests.get ("http://api.luftdaten.info/static/v1/data.json") df = sqlContext.createDataFrame ( [json.loads (line) for line in r.iter_lines ()]) Is it unpacking? Connect and share knowledge within a single location that is structured and easy to search. Thanks for contributing an answer to Stack Overflow! Can a trans man get an abortion in Texas where a woman can't? Thank you for the feedback. How many concentration saving throws does a spellcaster moving through Spike Growth need to make? When comparing nested_sample.json with sample.json you see that the structure of the nested JSON file is different as we added the courses field which contains a list of values in it. What are the differences between and ? Does no correlation but dependence imply a symmetry in the joint variable space? Calculate difference between dates in hours with closest conditioned rows per group in R. Why did The Bahamas vote in favour of Russia on the UN resolution for Ukraine reparations? Also, since your final output is a csv file, you could skip the dataframe and use csv.DictWriter instead. Now, I want to modify the importdata function to support pagination (Multiple calls that are merged together). In this article, we will explore the complete same process with an easy example. Same Arabic phrase encoding into two different urls, why? I understand that but I don't know how to solve this. How can I attach Harbor Freight blue puck lights to mountain bike for front lights? To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Not the answer you're looking for? Why do my countertops need to be "kosher"? Is it legal for Blizzard to completely shut down Overwatch 1 in order to replace it with Overwatch 2? Failed radiated emissions test on USB cable - USB module hardware and firmware improvements. And the second file will be a nested JSON file: Lets save it as nested_sample.json in the same location as your Python code. Hence, by using json.loads () function, one can simply convert JSON data into Python data. How can I pretty-print JSON in a shell script? Site design / logo 2022 Stack Exchange Inc; user contributions licensed under CC BY-SA. Stack Overflow for Teams is moving to its own domain! Create a series of functions? Site design / logo 2022 Stack Exchange Inc; user contributions licensed under CC BY-SA. The following is the answer I wrote to extract the columns of interest from the API response. this is a sample data of the importdata call (original function): how to convert response from request.get to DataFrame? There are multiple customizations available in the to_json function to achieve the desired formats of JSON. Speed up Python loop with DataFrame / BigQuery, Deeply nested json - a list within a dictionary to Pandas DataFrame, how to convert a json file into a pandas dataframe. Great point about vendors. Explanation In the above code, we have read the local JSON file into the df variable by using the pd.read_json method, we pass the JSON file location as a string to this method. # load data using Python JSON module with open ('multiple_levels.json','r') as f: data = json.loads (f.read ()) # Normalizing data DataFrame .to_csv method which takes in the path along with the filename where you want to save the CSV as input parameter and saves the generated CSV data in Step 3 as CSV. Under what conditions would a society be able to remain undetected in our current world? Example Convert from Python to JSON: import json # a Python object (dict): x = { "name": "John", "age": 30, "city": "New York" } # convert into JSON: y = json.dumps (x) # the result is a JSON string: print(y) Try it Yourself Lambda to function using generalized capture impossible? To get the data as a JSON output, we call the **request.get **method. Surely there is a more direct way of doing that, such as using a for loop to build the dict (exactly how, we can't tell without sample data). As the response already is json format, you do not need to encode it. Posted on March 1, 2021 by PyShark in Data science | 0 Comments. In the original code (before the change) the importdata data just get the data without manipulate it so inside the generatejson I consider only ["results"]. This method will automatically convert the data in JSON files into DataFrame. Python Pandas - Convert dataframe into json; fetch data from API n times and then convert it into a single pandas dataframe; Make sure your Pandas version is >= 1.0.3. Lets see how we can quickly convert JSON to Pandas DataFrame in Python. If so, what does it indicate? lines bool, default False. Converting nested JSON structures to Pandas DataFrames The Problem APIs and document databases sometimes return nested JSON objects and you're trying to promote some of those nested keys. Site design / logo 2022 Stack Exchange Inc; user contributions licensed under CC BY-SA. https://textuploader.com/dz30p. How to convert this nested array JSON response column to DataFrame in pandas Python; convert deeply nested JSON response to pandas dataframe; Convert JSON response to pandas dataframe; Convert json response (from google sheets API's 'spreadsheet.value.get ') into a pandas dataframe with correct column headers; Convert nested json response to . In our implementation on Jupyter Notebook, we have demonstrated the use of necessary parameters. Asking for help, clarification, or responding to other answers. You can check it by running: If your version is less than 1.0.3, please update your Pandas by running the following code in your Command Prompt (or Terminal): As the first step we will create a few sample JSON file that we will later convert to a Pandas DataFrame. Convert CSV from an api to a dataframe format in python. Asking for help, clarification, or responding to other answers. Is it bad to finish your talk early at conferences? To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Can we prosecute a person who confesses but there is no hard evidence? Why are operads sometimes better than algebraic theories? rev2022.11.15.43034. I see the combined JSON so this works great. Create a Spark DataFrame from a Python directory. high, Second parameter: orient. 505), Get data by pages and merge it into one using Python (pagination), Conversion between Json and DataFrame using Python. None is the usual placeholder for missing values of any type. Reading json data in Python is very easy. Use json.dumps to convert the Python dictionary into a JSON string. Python, Convert JSON response to pandas dataframe Author: Scott Gardner Date: 2022-07-19 Question: I am getting json response from a site Output: Than i am trying to convert it to dataframe: But in the result i have 1 row with lots of columns. One additional way of converting data from a JSON object to a DataFrame is to use the from_dict function. pip install beautifulsoup4. With a large availability of APIs to query large volumes of data from a variety of sources, JSON objects became a popular source for the projects data. SQLite - How does Count work without GROUP BY? Use DataFrame.from_dict () to Convert JSON to DataFrame First load JSON string to a dict object and then use pd.DataFrame.from_dict (data, orient="index") to create a DataFrame from the dict object where keys from the dict are used as an index. Specify the orientation of the JSON . If 'orient' is 'records' write out line-delimited json format. Firstly convert JSON to dataframe and then to parquet file. How to Convert a JSON File to a Pandas DataFrame Occasionally you may want to convert a JSON file into a pandas DataFrame. We are going to extract the data from an XML file using this library, and then we will convert the extracted data into Dataframe. Block all incoming requests but local network. We can directly pass the path of a JSON file or the JSON string to the function for storing data in a Pandas DataFrame. Asking for help, clarification, or responding to other answers. Python. # converting json data to a pandas dataframe import requests import pandas as pd resp = requests.get ( 'https://reqres.in/api/users' ) resp_dict = resp.json () df = pd.dataframe (resp_dict.get ( 'data' )) print (df) # returns: # id email first_name last_name avatar # 0 1 george.bluth@reqres.in george bluth https://reqres.in/img/faces/1-image.jpg How to iterate over rows in a DataFrame in Pandas. I tried to modify as follows: sample_object = pd.DataFrame(response.json()).to_dict() AttributeError: 'list' object has no attribute 'json' I couldn't think of a way to remove these repeated loops and still have legible code. Handler to call if object cannot otherwise be converted to a suitable format for JSON. The pd.DataFrame() needs a listOfDictionaries as input. Sample of what importdata(data) returns: How do we know "is" is a verb in "Kolkata is a big city"? How do I concatenate two lists in Python? This is the best i could get: first convert your json to dict and then the dict to DataFrame: If yout json do not contain lists for each dictionary key you may want to try orienting dataframe by the index instead: Here is one approach. If we do not wish to completely flatten the data, we can use the max_level attribute as shown below. Level up your programming skills with exercises across 52 languages, and insightful discussion with our dedicated team of welcoming mentors. import requests params = { "api_key": "abc", "format": "csv" } r = requests.get ('https://www.parsehub.com/api/v2/runs/ttx8PT-EL6Rf/data', params=params) print (r.text) generatejson() ? If I do: print json.dumps(datarALL) This method is basically used to read JSON files through pandas. t-test where one sample has zero variance? Create a Spark DataFrame from a Python dictionary. Also, since your final output is a csv file, you could skip the dataframe and use csv.DictWriter instead. Why don't chess engines take into account the time left by each player? rev2022.11.15.43034. A web application for forecasting in Python, R, Ruby, C#, JavaScript, PHP, Go, Rust, Java, MATLAB, etc. It parses a JSON string and converts it to a Pandas DataFrame: import pandas as pd df = pd.read_json("sample.json") Let's take a look at the JSON converted to DataFrame: print(df) We get exactly the content of the JSON file converted to a DataFrame. Service continues to act as shared when shared is set to false. Does induced drag of wing change with speed for fixed AoA? If you have jsonStr, you need an extra step to listOfDictionaries first. Hence the error message. Converting Json file to Dataframe Python. The first file will be a very simple one: Lets save it as sample.json in the same location as your Python code. Reading a simple JSON file is very simple using .read_json () Pandas method. This said, there is one caveat here, we must confirm that the object we have stored is of type 'dict' once read into a variable in Python. Convert the list to a RDD and parse it using spark.read.json. How do we know "is" is a verb in "Kolkata is a big city"? Is atmospheric nitrogen chemically necessary for life? To continue following this tutorial we will need the two Python libraries: json and pandas. No need to build dataALL then. %python jsonRDD = sc.parallelize (jsonDataList) df = spark.read.json (jsonRDD) display (df) How to convert Json to Pandas dataframe. If you have nested columns then you first need to normalize the data: This will Normalize semi-structured JSON data into a flat table. Tihs returns me a complex JSON: shared here. How to handle? I use repeated list comprehensions in loops over the JSON object data; where data = response.json(). Does picking feats from a multiclass archetype work the same way as if they were from the "Other" section? df = pd.read_json ('data/simple.json') image by author The result looks great. This code using pagination. Although, we have showed the use of almost all the parameters but only path_or_buf and orient are the required one rest all are optional to use. How would I expand this for the other items? How do I check whether a file exists without exceptions? volume Why do my countertops need to be "kosher"? The best answers are voted up and rise to the top, Not the answer you're looking for? Fortunately this is easy to do using the pandas read_json () function, which uses the following syntax: read_json ('path', orient='index') where: path: the path to your JSON file. Can anyone give me a rationale for working in academia in developing countries? that doesnt return the columnas as I explained above, it puts ALL into one df cell. You could simplify it to: dataALL += responsedata.json () The problem comes later: pd.DataFrame (response.json ()) Converting The JSON File Into A Clean DataFrame. Approach like this, req = requests.get (SAMPLE_SCHEDULE_API) data_str = req.json ().get ('data') json_data = json.loads (data_str) json () method will return the json-encoded content of a response. Would drinking normal saline help with hydration? When the migration is complete, you will access your Teams at stackoverflowteams.com, and they will no longer appear in the left sidebar on stackoverflow.com. To install this library, the command is. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, datarALL = datarALL + jsondata["results"] Gives only the results part of what I get from the API call.. input: jsonStr --> use @JustinMalinchak solution example: ' {"": {". DataFrame - to_json () function. 1. I think you need json_normalize:. The list for 'timestamp' is json['chart']['result'][0]['timestamp'], the one for 'open' is json['chart']['result'][0]['indicators']['quote'][0]['open'], etc. By default, columns that are numerical are cast to numeric types, for example, the math, physics, and chemistry columns have been cast to int64. Does the Inverse Square Law mean that the apparent diameter of an object of same mass has the same gravitational effect? Step 1: Prerequisite JSON object creation - Here is the code for dummy json creation which we will use for converting into parquet. Basic question: Is it safe to connect the ground (or minus) of two different (types) of power sources. To get the json type, we need to use data.json() method. To learn more, see our tips on writing great answers. Here, we have a single row. But the real head-scratcher is why you're doing this: Which isn't really "using Pandas" other than to reformulate a list into a dict. Let us try it and see what we get . The final JSON format depends on the value of the orient parameter, which is 'columns' by default but can be specified as 'records', 'index', 'split', 'table', and 'values'. Do solar panels act as an electrical load on the sun? In [4]: . It takes several parameters. 505), Parsing JSON and exploring relationships in Python, Parsing and saving JSON result from GoEuro API, Web scraping JSON-data from API put into Dataframe, Efficiently parsing JSON response data in python. The pd.DataFrame () needs a listOfDictionaries as input. 2. }, But in the json of the API call, the timestamp and the values are returned in 2 different elements. How to connect the usage of the path integral in QFT to the usage in Quantum Mechanics? By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, Thanks, @Marlon Abeykoon, very useful especially if I want to import a JSON, Python - How to convert JSON File to Dataframe, Speeding software innovation with low-code/no-code tools, Tips and tricks for succeeding as a developer emigrating to Japan (Ep. In this SO question the OP is unable to scrape a table from a dynamically loaded website. . What was the last Mac in the obelisk form factor? Why don't chess engines take into account the time left by each player? How do I select rows from a DataFrame based on column values? Example: JSON to CSV conversion using Pandas. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. it is due to the way your json is. Connect and share knowledge within a single location that is structured and easy to search. It works differently than .read_json() and normalizes semi-structured JSON into a flat table: In this article we discussed how to convert JSON to Pandas DataFrame in Python using json and pandas libraries. Toilet supply line cannot be screwed to toilet when installing water gun. How can I convert it to a table like such. It seems like what you're doing here is to incrementally build a list. As you are working in Python, most likely you would want your data to be in a format of a list or a DataFrame. Pretty nice code BTW. All data science projects begin with accessing the data and reading it correctly. (I wondered at this moment whether JSON files were dictionaries, and found some interesting insight here and here, fyiit turns out that even though JSON files look like a . Reading a simple JSON file is very simple using .read_json() Pandas method. To convert pandas DataFrames to JSON format we use the function DataFrame.to_json () from the pandas library in Python. But the far more efficient way to simply construct a DataFrame per page using your original code, and then call pd.concat(pages) where pages is the list of those DataFrames. Convert the file data into dictionary using json.load () function. What is the purpose of the * in the above please? It parses a JSON string and converts it to a Pandas DataFrame: Lets take a look at the JSON converted to DataFrame: We get exactly the content of the JSON file converted to a DataFrame. How can I make the return value of impordatatnew() compatible with Syntax: pandas.read_json ("file_name.json") Here we are going to use this JSON file for demonstration: Code: Python3 Why don't chess engines take into account the time left by each player? How do I make a flat list out of a list of lists? How can I remove a key from a Python dictionary? Following is my code. It is a python library that is used to scrape web pages. orient: the orientation of the JSON file. 0. conversion of dictionary to json to be sent to requests.post. Check the data type and confirm that it is of dictionary type. In this case, to convert it to Pandas DataFrame we will need to use the .json_normalize() method. Histograms, Gradient Boosted Trees, Group-By Queries and One-Hot Encoding. How to connect the usage of the path integral in QFT to the usage in Quantum Mechanics? API request to rapidapi.com The request.get method has the following parameter values: requests.get (url, params= {key: value}, args). Can we prosecute a person who confesses but there is no hard evidence? By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. A path to the JSON file: We can specify the JSON file name along with the path. Let's look at the parameters accepted by the functions and then explore the customization Parameters: Why the difference between double and electric bass fingering? 2. Block all incoming requests but local network. When the migration is complete, you will access your Teams at stackoverflowteams.com, and they will no longer appear in the left sidebar on stackoverflow.com. What does 'levee' mean in the Three Musketeers? @QHarr Just expand the function, adding the other items next to the two, Creating a python dataframe by parsing JSON API response, Speeding software innovation with low-code/no-code tools, Tips and tricks for succeeding as a developer emigrating to Japan (Ep. Creating dataframe from dictionary object. The JSON file's name: If the JSON file is in the current directory, we can specify its name only. My PhD fellowship for spring semester has already been paid to me. In monitoring the web traffic, via Chrome dev tools, I found that there is an API request made that returns a JSON string with the required info. Learning to sing a song: sheet music vs. by ear. Let us now see how to convert json to pandas DataFrame using Python. Feel free to leave comments below if you have any questions or have suggestions for some edits and check out more of my Python Programming articles. How do I get the row count of a Pandas DataFrame? This is the line that I am referring to: Instead of splitting the data into a separate variables by column, you could convert each JSON object into a flat dictionary using a function similar to this. Parameters of df.to_json() method. Making statements based on opinion; back them up with references or personal experience. Thanks for contributing an answer to Stack Overflow! Check the type of the value returned by the json.load () function. This is obvious as it is generated like: jsonStr = json.dumps (listOfDictionaries) Thus, switch back from jsonStr to listOfDictionaries first: It's syntax is as follow: Use MathJax to format equations. A JSON string: It can convert JSON string into pandas dataframe. from pandas import json_normalize df = json_normalize(d, 'abc') print (df) amount price tid timestamp type 0 2321.379525 0.000062 8577050 1498649162 bid 1 498.789936 0.000062 8577047 1498649151 bid Making statements based on opinion; back them up with references or personal experience. Why does Google prepend while(1); to their JSON responses? Why are operads sometimes better than algebraic theories? Is atmospheric nitrogen chemically necessary for life? For converting into the Dataframes, we need to install the panda's library. Selecting multiple columns in a Pandas dataframe. The to_json () function is used to convert the object to a JSON string. Ultimately your code can be simplified so much more, to end up like this: That is, first you use a for loop to build all_page_urls, then you use the above one-liner to collect all the data into a single DataFrame. We use pandas. The response has a collection of such dictionaries. 0. In this article, we are going to convert JSON String to DataFrame in Pyspark. Should receive a single argument which is the object to convert and return a serialisable object. Does induced drag of wing change with speed for fixed AoA? Is `0.0.0.0/1` a valid IP address? Python automatically does this regularly with JSON objects, but not all the time. What do you do in order to drag out lectures? The Vendors field has missing items hence my use of an if statement in the assignment to vendors. pandas by default support JSON in single lines or in multiple lines. Json data can be read from a file or it could be a json web link. # Basic syntax: dataframe = pd.DataFrame.from_dict(json_data, orient="index") # Example usage: import json import pandas as pd #. Open the sample JSON file which we created above. Site design / logo 2022 Stack Exchange Inc; user contributions licensed under CC BY-SA. convert response to json python; save json file python; python json from csv; convert dictionsr to json file python; list to json python; python object to json; nested json to csv python; convert csv to json python; python to json; convert to json python; convert dict to json python; pandas df to mongodb; json to csv python; write json pythonb With the JSON file data being stored as key-value pairs, the good thing is it has the same structure of a dictionary. You could simplify it to: This is because you are calling json() again on something which has already been parsed from JSON to a Python list.