Как json перевести в excel
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Как json перевести в excel

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Конвертировать JSON в Excel

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Эта форма позволяет вам конвертировать данные JSON в Excel файл, вставьте или загрузите файл JSON ниже:

О преобразовании JSON в Excel

О конвертировании JSON данных в Excel файл

Конвертер JSON в Excel была создана для быстрого преобразования данных JSON(JavaScript Object Notation) в Excel(электронные таблицы Microsoft Excel).

Как это работает?

Просто вставьте или загрузите JSON данные в текстовое поле выше и нажмите кнопку Конвертировать и Скачать, и вы сразу получите Excel файл.

Пример преобразования JSON в Excel

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Convert JSON to Excel

Online Converter: Convert JSON file into Excel format

You may help others to find this website — Share your experience!

The converter helps to transform the content of JSON file to Excel online and saves the result in .xlsx or .xls format.

Why Should You Transform JSON to Excel?

It is difficult to read and comprehend JSON even though it is a text format. Our service can assist in this case by converting JSON into Excel table. As a result, it becomes easy to read, understand and do required data manipulations like filtering and applying formulas.

JSON File Format

JavaScript Object Notation is the full meaning of JSON. This is a text document that can be created in any text editor. It is a popular text-based technique for presenting structured data in JavaScript object syntax.

JSON Format Description

This format contains different types of data: objects, arrays, and attributes.

The Attribute is a key-value, where the key is the name of the attribute. Attributes can only be used inside objects.

The Object is a data structure with a set of attributes on the same level.

And Array is a set of objects.

Where is the JSON Format Applicable?

It is a commonly used format for internet services, APIs, websites. The JavaScript Object Notation file can be used to store and configure data. It can as well be used for data interchange between different applications.

JSON is one of the most popular formats used on the Internet — for data interchange between websites or internet services or APIs.

File Format Information

Additional information about this format can be found in the resources below:

    at File.org at FILExt.com

How Exactly Does the Converter Work?

We transform objects in JSON into a flat table layout in accordance to specified rules, with arrays acting as a collection of rows in the table.

An example of a conversion:

Sample JSON file

Source file:

Sample JSON file converted to Excel

Result table data:

Use our JSON to CSV converter if you prefer to receive the result in CSV style.

Excel Format

This is used in Microsoft Office Excel program. The extension used in an Excel file is either .XLS or .XLSX, depending on the version used.

Our Converter saves the documents in the XLSX format, which is compatible with Microsoft Office 2007 and later editions, or you can choose XLS format for earlier versions.

Excel Limits (XLSX for Excel 2007+)

It has the following restrictions when it is used with Microsoft Office:

  • Maximum number of rows: 1,048,576 rows
  • Maximum number of columns: 16,384 columns (last column is "XFD")
  • Column width: 255 characters
  • Maximum number of characters in a cell: 32,767 characters
  • Maximum number of Hyperlinks in a worksheet: 66,530 hyperlinks
Excel Limits (XLS — Excel 97-2007)

The restrictions of the XLS style used in 97-2007 are listed below

  • Maximum number of rows: 65,536 rows
  • Maximum number of columns: 256 columns (last column is "IV")
File Format Information

Additional information can be found in the following resources

    at File.org at File.org at FILExt.com at FILExt.com

(FAQ) Frequently Asked Questions

How Do I Transform JSON into Excel?

All kinds of JSON files can be exported to Excel format with the use of our converter.

Follow the steps listed below to use our converter:

  • Upload the file
  • Click on the 'Run Conversion' button
  • Download the transformed file

How Long Does It Take to Convert JSON to Excel?

The size of the file determines how long it will take to convert JSON to Excel online; usually the conversion is quite easy to perform and does not take much time.

Is It Safe to Convert JSON to Excel Using Our Converter?

Yes, it is safe. All documents uploaded to our services are encrypted with the use of the best advanced encryption technology and deleted after 24 hours.

What Makes Our Converter a Good Choice?

We are devoted to providing you with the best service possible. Here's why you should consider using our converter:

Easily enriching publicly available data (and really any other kind of data)

José Lara

[Disclaimer: the Excel-JSON import offered by the Power Query Excel add-in is only available for Windows — upvote this UserVoice feature request so the team prioritizes adding the PowerQuery Excel add-in for Mac.]

As part of a UW class on information visualization taught by Brock Craft, I found myself changing gears from big data, to much smaller data.

Data wrangling is a necessary step when working with publicly available data and enriching/preparing said data for consumption by apps, services, or even visualizing it directly with libraries such as D3.js. Online services such as the Microsoft Azure Maps service API or the Google Maps API can help to enrich location data by either geocoding, or reverse-geocoding depending on the data available, and format needed. In my case, I had a very simple dataset that had (among many) a column for the name of a US city, and another for the US state for each row.

My goal: enrich each row in the dataset with the latitude and longitude to be able to use D3.js more efficiently.

Tools used

    — super easy to create and format requests to web APIs. — my favorite lightweight editor — the ultimate application to work with smaller datasets by using pivot tables, look-ups, etc. — used to query each city and state in order to obtain the address, geographic coordinates, and other useful pieces of data, such as county, state initials, etc.

Getting the data from Azure Maps using their API

[As a prerequisite, you need an Azure subscription — you can get some free credit when signing up for Azure]

The first step was to create an Azure Maps account from inside the Azure Portal and obtain an API key. You can see how to do it in the Azure Maps documentation here.

With the Azure Maps API key, I used the Postman app to create a few sample requests and ensure the key was working nicely. You can see how to submit them in the How to Search For an Address section in the Azure Maps docs.

Once the basics worked, I made an Excel pivot table from the original dataset to list the distinct combinations of city and state and used the preview batch request API to send a query with them. This was a better approach than querying for the same city and state hundreds, or thousands of times.

I copied the response data into VS Code and saved it as .JSON to then work with the file in Excel.

Wrangling the data in Excel (Windows only)

Open the JSON file using the Power Query add-in:

Data →Get Data →From File →From JSON

Once you select the file, you’ll see the root nodes in the JSON file. Note that these are links that you can navigate to.

The first step in the Power Query Editor is to convert the nodes into columns.

Record Tools →Convert →Into Table

They will look like this once they are converted:

Click on the item List since it contains all the records we’re interested in. The summary shows the summary of the API request; for this process it is not relevant.

We’ll do the same transforming into table at this level:

After it is converted to a table, you’ll see a small icon that lets you expand the contents into columns. Click it to see the contents of the record object and to expand it:

After expanding, the table will show a record object and a list object in each row. This is because each row represents:

  • A query record (the query we did for each row, such as Paris, Texas, US, or Seattle, Washington, US).
  • A list of the associated search results for the query which can contain 1 or more results depending on the request settings. In this case, to make my life easier, in the request I specified only one.

If you notice the Postman screenshot, shows the first few rows of the result — you can see how results is in fact a list of records.

With this table, we will do the exact same thing again for each objects column→ Expand to new rows.

After expanding the query summaries, we scroll right, and then expand the results objects column:

This expansion will change the object from list to record because each list has only one record:

We expand this again:

After expanding, we’ll see data, plus some more objects:

From this table, we will expand the address objects once more to get the actual addresses, and the position object to get the latitude and longitude too:

At this point, we’ll see the actual latitude and longitude. Whew!

Load the data into the Excel worksheet

Once we’ve expanded the necessary objects (and if you want, hid unnecessary columns), we can save and load the table into Excel:

Once you load the data into the Excel sheet, it will be ready to use:

From this point on you can filter the data, create a pivot table, or do any other thing that you need to refine the dataset that you’re working with.

Conclusion

This guide covered some basic steps to import a JSON file into excel and how to expand the contents to see the actual data returned by the Azure Maps API.

I loved using the API directly — it took me in total about 20 minutes to geocode about

4,000 distinct addresses, which I then added to my main dataset.

The steps shown here worked well for my needs, but be aware that there are other ways to do this using Python, or even using other services, such as Google Maps. Depending on your specific needs you might need to fine tune the API request, or filter specific fields returned by the API.

With this wrangling step complete, you should be able to import your data into D3.js or other application and start to work on the visualization.

Конвертировать JSON массив в Excel

Перед использованием преобразователя JSON, пожалуйста, убедитесь, что ваш JSON находится в формате массива объектов. Нажмите JSON Пример IN Источник данных Panel Для просмотра демонстрации. Конечно, в дополнение к вставлению, вы также можете нажать «Загрузить JSON» или перетаскивание файла JSON.

2. Отредактируйте свой JSON массив онлайн, если это необходимо

Вы можете редактировать свои данные онлайн, например, Excel через Редактор таблицы, а изменения будут преобразованы в Excel в режиме реального времени.

3. Скопируйте преобразованный Excel

Сгенерированный Excel разделен вкладками, это здесь: Генератор таблицы. Вы можете скопировать и вставить в Microsoft Excel, простыни или номера Google или загрузить в виде файла `xlsx.

Примечание. Ваши данные безопасны, конверты полностью выполняются в вашем веб-браузере, и мы не будем хранить какие-либо ваши данные.

Что такое JSON?

JSON Подписчики для объекта JavaScript. Файл JSON — это текстовый формат для представления структурированных данных на основе синтаксиса объекта JavaScript.

Что такое Excel?

Microsoft Excel — это электронное приложение электронной таблицы, которое позволяет пользователям хранить, организовывать, рассчитать и манипулировать данными с формулами, используя систему электронной таблицы, разбитой строками и столбцами.

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