However, it is not as straightforward when it comes to analyzing JSON. Hence, in this tutorial, we will learn how to convert a JSON file into a Pandas table.
Sample Data
The first step is to have the JSON data we wish to parse. We have selected a simple JSON file containing astronomy information for a specific city for this tutorial.
Sample data is as shown:
"country": "United Kingdom,"
"state": "England",
"city": "London",
"latitude": 51.466652350000004,
"longitude": -0.09686637642617651,
"date": "2022-04-13",
"current_time": "03:12:55.044",
"sunrise": "06:09",
"sunset": "19:53",
"sun_status": "-",
"solar_noon": "13:01",
"day_length": "13:44",
"sun_altitude": -23.19751117067553,
"sun_distance": 1.4988500851835912E8,
"sun_azimuth": 35.781559107335625,
"moonrise": "15:43",
"moonset": "05:28",
"moon_status": "-",
"moon_altitude": 20.615536932562232,
"moon_distance": 387894.3437906608,
"moon_azimuth": 266.5048405334666,
"moon_parallactic_angle": 34.5669393631715
}
Save the JSON file as astronomy_simple.json
Read JSON With Pandas
We will use Pandas to read the JSON file and convert it into a table.
Start by importing pandas:
import pandas as pd
Next, we will read the JSON file using the read_json function. This allows us to convert a JSON string to a pandas object as shown:
Once we have the JSON file converted into a pandas object, we can convert it into a pandas DataFrame as shown:
Finally, to print the data in a tabular format, use the display func as shown:
This should return:
Conclusion
This short article describes a simple method to convert a JSON file into a table using Pandas.
