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Read JSON File into DataFrame Using Python Pandas
JSON stands for JavaScript Object Notation, it stores the text data in the form of key/value pairs and this can be a human-readable data format. These JSON files are often used to exchange data on the web. The JSON object is represented in between curly brackets ({}). Each key/value pair of JSON is separated by a comma sign.
JSON data looks very similar to a python dictionary, but JSON is a data format whereas a dictionary is a data structure. To read JSON files into pandas DataFrame we have the read_json method in the pandas library. Below examples give you the overview of how we can read JSON files into a pandas DataFrame.
Example
Reading local JSON file into the pandas DataFrame
#importing pandas package import pandas as pd # reading JSON file df = pd.read_json('E:\iris.json') # displaying sample output df.sample(5)
Explanation
In the above code, we have read the local JSON file into the df variable by using the pd.read_json method, we pass the JSON file location as a string to this method. This method will automatically convert the data in JSON files into DataFrame. Initially, we imported the pandas package as pd. Finally, In the last line, we displayed the 5 sample lines from DataFrame as output.
Output
sepalLength sepalWidth petalLength petalWidth species 149 5.9 3.0 5.1 1.8 virginica 90 5.5 2.6 4.4 1.2 versicolor 56 6.3 3.3 4.7 1.6 versicolor 38 4.4 3.0 1.3 0.2 setosa 85 6.0 3.4 4.5 1.6 versicolor
Iris JSON data set/file is taken as input to the read_json method, this data set has 5 columns and 150 rows of data. In this output block, we only displayed a sample of 5 rows of data by using the df.sample() method. This method randomly returns the data from the DataFrame.
In this same way, we can read remote JSON data, by mentioning the remote URL in the place of the file path.
Example
import pandas as pd data = pd.read_json( 'http://universities.hipolabs.com/search?country=United+Kingdom') print(data)
Explanation
In this example, we have taken a public HTTP API that is holding data in JSON format. Here also the read_json method is used to read this remote URL JSON data.
Output
domains | web_pages | name | alpha _two_ code | state-province | country | |
---|---|---|---|---|---|---|
0 | [abdn.ac.UK, Aberdeen.ac.uk] | [www.abdn.ac.uk/] | University of Aberdeen | GB | NaN | United Kingdom |
1 | [aber.ac.uk] | [www.aber.ac.uk/] | University of Wales, Aberystwyth | GB | NaN | United Kingdom |
2 | [abertay.ac.uk] | [www.abertay.ac.uk/] | University of Abertay Dundee | GB | NaN | United Kingdom |
3 | [aiuniv.edu] | [www.aiuniv.edu/] | American InterContinental University - London | GB | NaN | United Kingdom |
4 | [aku.edu] | [www.aku.edu/] | Aga Khan University | GB | NaN | United Kingdom |
This output has sample 4 rows of JSON data from the read_json method, this is the data from a public URL and it has 171 rows and 6 columns.