Getting ready

To execute this recipe, you will need Python with the pandas module installed. No other prerequisites are required.

How to do it…

The code to read a JSON file is as follows. Note that we assume the pandas module is already imported and aliased as pd (the read_json.py file):

# name of the JSON file to read from
r_filenameJSON = '../../Data/Chapter01/realEstate_trans.json'

# read the data
json_read = pd.read_json(r_filenameJSON)

# print the first 10 records
print(json_read.head(10))

How it works…

This code works in a similar way to the one introduced in the previous section. First, you need to specify the name of the JSON file—we store it in the r_filenameJSON string. Next, use the read_json(...) method of pandas, passing r_filenameJSON as the only parameter.

The read data is stored in the json_read DataFrame object. We then print the bottom 10 observations using the .tail(...) method. To write a JSON file, you can use the .to_json() method on DataFrame and write the returned data to a file in a similar manner as discussed in the Reading and writing CSV/TSV files with Python recipe.

There's more…

You can read and write JSON files using the json module as well. To read data from a JSON file, you can refer to the following code (the read_json_alternative.py file):

# read the data
with open('../../Data/Chapter01/realEstate_trans.json', 'r') \
    as json_file:
        json_read = json.loads(json_file.read())

This code reads the data from the realEstate_trans.json file and stores it in a json_read list. It uses the .read() method on a file that reads the whole content of the specified file into memory. To store the data in a JSON file, you can use the following code:

# write back to the file
with open('../../Data/Chapter01/realEstate_trans.json', 'w') \
    as json_file:
        json_file.write(json.dumps(json_read))

See also

Check the pandas documentation for read_json at http://pandas.pydata.org/pandas-docs/stable/io.html#io-json-reader.