How to convert to a .json file using Python?

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Sometimes we need to convert our data to .json format, and I will introduce an easy way to do it using Python. I will use Google Colab.

First, let’s mount Google Drive to Google Colab.

from google.colab import drive
drive.mount('/content/drive')

Second, let’s upload a dataset from GitHub.

import pandas as pd
import requests
from io import StringIO

github="https://raw.githubusercontent.com/agronomy4future/raw_data_practice/refs/heads/main/biomass_N_P.csv"
response=requests.get(github)
df=pd.read_csv(StringIO(response.text))

df.head(5)

season	cultivar  treatment  rep  biomass  nitrogen  phosphorus
2022	cv1	  N0	     1	  9.16	   1.23	     0.41
2022	cv1	  N0	     2	  13.06	   1.49	     0.45
2022	cv1	  N0	     3	  8.40	   1.18	     0.31
2022	cv1	  N0	     4	  11.97	   1.42	     0.48
2022	cv1	  N1	     1	  24.90	   1.77	     0.49
.
.
.

I’ll convert this data to a .json file

df.to_json('df.json', orient='records')

and download it to my PC.

from google.colab import files

files.download('df.json')

or I can directly download it to Google Colab.

df.to_json('<mark style="background-color:rgba(0, 0, 0, 0)" class="has-inline-color has-vivid-cyan-blue-color">/content/drive/MyDrive/Colab/Python_code/</mark>df.json', orient='records')
<mark style="background-color:rgba(0, 0, 0, 0)" class="has-inline-color has-vivid-cyan-blue-color"># your pathway</mark>

Now .json file is created.

Let’s upload this .json file to Google Colab.

When uploading from my PC,

from google.colab import files
uploaded = files.upload()

import pandas as pd
df = pd.read_json('df.json')

df.head(5)

df.json(application/json) - 6670 bytes, last modified: 2/27/2025 - 100% done
Saving df.json to df.json
season cultivar treatment  rep  biomass  nitrogen  phosphorus
2022   cv1      N0         1    9.16      1.23     0.41
2022   cv1      N0         2    13.06     1.49     0.45
2022   cv1      N0         3    8.40      1.18     0.31
2022   cv1      N0         4    11.97     1.42     0.48
2022   cv1      N1         1    24.90     1.77     0.49
.
.
.

and when uploading from Google Colab,

from google.colab import drive
import pandas as pd

file_path = '<mark style="background-color:rgba(0, 0, 0, 0)" class="has-inline-color has-vivid-cyan-blue-color">/content/drive/MyDrive/Colab/Python_code/</mark>df.json'
df = pd.read_json(file_path)
<mark style="background-color:rgba(0, 0, 0, 0)" class="has-inline-color has-vivid-cyan-blue-color"># your pathway </mark>

df.head(5)

season	cultivar  treatment  rep  biomass  nitrogen  phosphorus
2022	cv1	  N0	     1	  9.16	   1.23	     0.41
2022	cv1	  N0	     2	  13.06	   1.49	     0.45
2022	cv1	  N0	     3	  8.40	   1.18	     0.31
2022	cv1	  N0	     4	  11.97	   1.42	     0.48
2022	cv1	  N1	     1	  24.90	   1.77	     0.49
.
.
.

Full code: https://github.com/agronomy4future/python_code/blob/main/How_to_convert_to_json_file_using_Python.ipynb

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