It is the most used online format, aimed at interchanging data between websites, internet services, and APIs. JavaScript Object Notation is used to exchange, store, and configure data between applications and systems in its simple data-exchange format.
The Object is a data structure with a set of attributes on the same level. Attributes can only be used inside objects. The Attribute is a key-value, where the key is the name of the attribute. This format contains different types of data: objects, arrays, and attributes.
It can also be illustrated as plain text and may be opened with any text editor however, a JSON editor helps to assure file verification.įiles in JSON format have an extension. It is a popular language that supports multiple data types. Many libraries, programs, and frameworks may understand it. In case you have further questions, you may leave a comment below.It represents Java Script Object Notation. This post has shown how to convert a list into a csv file and vice-versa in Python. Convert List to Dictionary in Python (3 Examples).Convert List to Range in Python (2 Examples).Convert List to pandas DataFrame in Python (3 Examples).Check if Linked List is Empty in Python (2 Examples).In the video, we explain in some more detail how to convert a list into a csv file and vice-versa in Python.įurthermore, I encourage you to check out other interesting Python list tutorials on Statistics Globe, starting with these ones: I hope you found this tutorial helpful!ĭo you need more explanations on how to convert a list into a csv file and vice-versa in Python? Then you should have a look at the following YouTube video of the Statistics Globe YouTube channel. With that, we have demonstrated how to convert a list into a csv file and vice-versa in Python. To include the column headers in the list, we first used the df.columns.tolist() function to create the list of column headers, and then insert it into the “new_list” object with the new_list.insert() function, wherein we specified that we want the list of column headers to be at index position 0. This will return a list of values but will not include the column headers of the csv file in the list. In the code above, we, first read the csv file then we converted its values into a list with the df.values.tolist() method. insert ( 0, header ) print (new_list ) #, ,, ] print ( type (new_list ) ) #
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