Convert json data to pdf in python

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Convert json data to pdf in python

JSON (JavaScript Object Notation) is a simple language-independent and human-readable text format derived from JavaScript. It enables easy storage and exchange of structured data comprising attribute-value pairs and arrays or any such serializable data. This article talks about how to deal with JSON formatted data using Python codes. Encoding

(Python to JSON) The encoding process refers to the conversion of Python to JSON objects. Python provides a JSON package having API to operate on JSON data. Following is a list of Python objects and corresponding JSON objects they are encoded to. Python JSON listarraydictionaryobjectunicode characterstringTrueTrueFalseFalseNoneNullint or

long numberint numberfloat numberreal number Let's have a look at how to perform the encoding process in Python. Note: The code snippets throughout this article have been implemented using Google colab with Python 3.7.10 and json 2.0.9 versions. Import json library Import json as js Create a dictionary having data of various types. dictionary =

{ "name": "Alex", "gender": "Male", "age" : 38, "Indian": True, "brothers": ("Ron","Peter"), "sisters": ['Elizabeth'], "house": [ {"city": "LA", "price": 2380.5}, {"city": "NYC", "price": 1120} ] } Convert the dictionary into JSON-formatted string string = json.dumps(dict, indent=4, sort_keys=True) Print the converted object print(str) Output:

Check the type of `dictionary' and `string' objects. type(dictionary) Output: dict type(string) Output: str Decoding (JSON to Python) The process of converting JSON objects back to Python objects is referred to as decoding. The list of which python objects get converted to which JSON object type has been provided in the `Encoding' section above. The

reverse conversion of those objects occurs in the process of decoding. Create a JSON-formatted String object json_data = '{ "car": { "company": "Hyundai", "name": "EON", "number": 2889}}' Convert it into Python object using loads() method python_obj = js.loads(json_data) Display the Python object print(python_obj) Output: {'car': {'company':

'Hyundai', 'name': 'EON', 'number': 2889}} Check the data types of json_data and python_obj type(json_data) Output: str type(python_obj) Output: dict Writing to a JSON file Consider the `dictionary' named Python object created in the `Encoding' section above. Write the dictionary's data to a JSON file using dump() method. See Also #Open the

JSON file (create if it does not exist) in write mode with open("myfile.json", "w") as wfile: js.dump(dictionary, wfile) myfile.json now looks like: Reading a JSON file The above created JSON file myfile.json can be read using load() function #Open the file to be read with open('myfile.json') as fobj:

# store the read data in JSON object

read_data = js.load(fobj) #Display the read data print(read_data) Output: {'name': 'Alex', 'gender': 'Male', 'age': 38, 'Indian': True, 'brothers': ['Ron', 'Peter'], 'sisters': ['Elizabeth'], 'house': [{'city': 'LA', 'price': 2380.5}, {'city': 'NYC', 'price': 1120}]} JSONEncoder class JSONEncoder class provides the following three methods to serialize data

during the encoding process. default(obj) ? This method is implemented in a subclass. It returns a serializable object for the specified argument. encode(obj) ? It performs the encoding process, i.e. Python object to JSON-formatted string conversion, as done by the dumps() method.iterencode(obj) ? It encodes the `obj' object and returns its string-

converted representation as it becomes available. Have a look at an example of encoding a Python dictionary using encode() method. #Import the JSONEncoder class from json.encoder import JSONEncoder #Create a Python dictionary shape_dictionary = { "shape": ["circle", "square", "triangle" ]} # Encode the dictionary json_encode =

JSONEncoder().encode(shape_dictionary) #Display the encoded output json_encode Output: {"shape": ["circle", "square", "triangle"]} Check the data type of json_encode object type(json_encode) Output: str JSONDecoder class JSONDecoder is a class for performing deserialization using the following three methods: default(str) ? It is implemented in

the subclass and decodes `str' (a String instance comprising a JSON document). If the document is invalid, it raises JSONDecodeError. decode(obj) ? It decodes the JSON object `obj' as done by the loads() method.raw_decode(obj) ? It decodes the String object `str' starting with a JSON document. It returns a tuple comprising Python-converted form of

the JSON document and an index in the `str' marking end of the JSON document. Here's how we can decode a JSON string using decode() method. #Import the JSONDecoder class from json.decoder import JSONDecoder #Create a JSON-formatted string colour_string = '{ "colour": ["red", "yellow"]}' # Decode the string json_decode =

JSONDecoder().decode(colour_string) #Display the decoded output json_decode Output: {'shape': ['circle', 'square', 'rectangle']} Check the data type of json_decode object type(json_decode) Output: dict Google colab notebook of the above code snippets is available here.Refer to the official JSON package's documentation here. Join Our Discord

Server. Be part of an engaging online community. Join Here. Subscribe to our Newsletter Get the latest updates and relevant offers by sharing your email. JSON objects are used in many web APIs to use that data to extract meaningful information; we need to convert that data into a dictionary. Python provides a built-in json package that has various

methods to serialize and deserialize JSON.Python String to JSONTo convert a Python string to JSON, use the json.loads() function. The loads() method accepts a valid json string and returns a dictionary to access all elements. The json.loads() function is used to parse valid JSON String into Python dictionary.To make use of json.loads() method, we

have to import the json package offered by Python. The process of converting json data to python objects called deserialization.# app.py import json json_string = ''' { "students": [ { "name": "Millie Brown", "active": true, "rollno": 11 }, { "name": "Sadie Sink", "active": true, "rollno": 10 } ] } ''' print(json_string) print("The type of object is: ",

type(json_string)) stud_obj = json.loads(json_string) print(stud_obj) print("The type of object is: ", type(stud_obj)) json_obj = json.dumps(stud_obj) print(json_obj) print("The type of object is: ", type(json_obj))Output{ "students": [ { "name": "Millie Brown", "active": true, "rollno": 11 }, { "name": "Sadie Sink", "active": true, "rollno": 10 } ] } The type of

object is: {'students': [{'name': 'Millie Brown', 'active': True, 'rollno': 11}, {'name': 'Sadie Sink', 'active': True, 'rollno': 10}]} The type of object is: {"students": [{"name": "Millie Brown", "active": true, "rollno": 11}, {"name": "Sadie Sink", "active": true, "rollno": 10}]} The type of object is: In this example, first, we are converting the json string to the

Python dictionary object using json.loads() method and then converting the dictionary to string using json.dumps() method.Data Conversion from JSON to Python Objectsobject => dictarray => liststring => strnumber (int) => intnumber (real) => floattrue => Truefalse => Falsenull => NoneDifference between json.load() and json.loads()The main

difference between json.load() and json.loads() function that load() function is used to read the JSON document from file and the loads() function is used to convert the JSON String document into the Python dictionary.The json.load() function can deserialize a file itself. The json.loads() function deserialize a string.ConclusionIf we have a JSON string or

JSON data, we can easily parse it using the json.loads() method found in the json package.See alsoHow to create a json file in PythonHow to read json files in PythonPython json to dictionaryPython json to csvPython json parse In this guide, you'll see the steps to convert a JSON string to CSV using Python. To begin, you may use the following template

to perform the conversion: import pandas as pd df = pd.read_json (r'Path where the JSON file is saved\File Name.json') df.to_csv (r'Path where the new CSV file will be stored\New File Name.csv', index = None) In the next section, you'll see how to apply the above template in practice. Steps to Convert a JSON String to CSV using Python Step 1:

Prepare a JSON String To start, prepare a JSON string that you'd like to convert to CSV. For example, let's say that you'd like to prepare a JSON string based on the following information about different products: Product Price Desktop Computer 700 Tablet 250 Printer 100 Laptop 1200 This is how the JSON string would look like for our example:

{"Product":{"0":"Desktop Computer","1":"Tablet","2":"Printer","3":"Laptop"},"Price":{"0":700,"1":250,"2":100,"3":1200}} Step 2: Create the JSON File Once you have your JSON string ready, save it within a JSON file. Alternatively, you may copy the JSON string into Notepad, and then save that file with a .json extension. For our example, save the

notepad as Product_List.json. Don't forget to add the .json extension at the end of the file name. Step 3: Install the Pandas Package If you haven't already done so, install the Pandas package. You may use the following command to install the Pandas package under Windows: pip install pandas Step 4: Convert the JSON String to CSV using Python You

may now use the following template to assist you in converting the JSON string to CSV using Python: import pandas as pd df = pd.read_json (r'Path where the JSON file is saved\File Name.json') df.to_csv (r'Path where the new CSV file will be stored\New File Name.csv', index = None) For our example: The path where the JSON file is saved is:

C:\Users\Ron\Desktop\Test\Product_List.json Where `Product_List` is the file name, and `json` is the file extension The path where the new CSV file will be stored is: C:\Users\Ron\Desktop\Test\New_Products.csv Where `New_Products` is the new file name, and `csv` is the file extension Note that you'll need to adjust the paths to reflect the location

where the files will be stored on your computer. Here is the complete Python code to perform the conversion to CSV for our example: import pandas as pd df = pd.read_json (r'C:\Users\Ron\Desktop\Test\Product_List.json') df.to_csv (r'C:\Users\Ron\Desktop\Test\New_Products.csv', index = None) Run the code (adjusted to your paths) and you'll see the

new CSV file at your specified location. Once you open the file, you'll get the data about the products: Product Price Desktop Computer 700 Tablet 250 Printer 100 Laptop 1200 You may also want to check the following guides for other types of file conversions: Convert CSV to Excel Convert Excel to CSV

how to convert csv data to json format in python. how to convert json data into table format in python. how to convert json data to dataframe in python. how to convert json data into dataframe in python. how to convert json data to csv in python. how to convert data to json in python. convert excel data to json in python. how to convert json data to

dictionary in python

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