Pandas DataFrame to_json() method is “used to convert the object to a JSON string.”
Syntax
DataFrame.to_json(self, path_or_buf=None, orient=None,
date_format=None, double_precision=10,
force_ascii=True,
date_unit='ms',
default_handler=None, lines=False,
compression='infer', index=True)Parameters
path_or_buf: File path or object. The result is returned as a string if the path is not specified. The parameter is optional.
orient: Indication of expected JSON string format. The parameter is required.
- Series
- default is ‘index’
- allowed values are: {‘split’,’ records’,’ index’,’table’}
- DataFrame
- default is ‘columns’.
- allowed values are: {‘split’,’ records’,’ index’,’ columns’,’ values’,’ table’}
- The format of the JSON string
- ‘split’: dictionary like {‘index’ -> [index], ‘columns’ -> [columns], ‘data’ -> [values]}
- ‘records’: list like [{column -> value}, … , {column -> value}]
- ‘index’: dictionary like {index -> {column -> value}}
- ‘columns’: dictionary like {column -> {index -> value}}
- ‘values’: just the values array.
- ‘table’: dictionary like {‘schema’: {schema}, ‘data’: {data}} describing the data, and a data component is like orient=’records’.
date_format: The time unit to encode to govern timestamp and ISO8601 precision. One of ‘s’, ‘ms’, ‘us’, ‘ns’ for a second, millisecond, microsecond, and nanosecond, respectively. The parameter is optional.
default_handler: Handler to call if the object cannot be converted to a suitable format for JSON. Should receive a single argument, which is the object to convert and return a serializable object. This parameter is optional.
lines: If ‘orient’ is ‘records’, write outline delimited json format. Will throw ValueError if incorrect ‘orient’ since others are not like lists. The parameter is optional.
compression: A string representing a compression in the output file, only used when the first argument is the filename. By default, compression is inferred from the filename. This parameter is optional.
index: Whether to include index values in the JSON string. Not including an index (index=False) is only supported when the orient is ‘split’ or ‘table’. This parameter is optional.
Return Value
If path_or_buf is None, it returns the resulting json format as a string. Otherwise returns None.
Example 1: How to Use Pandas DataFrame to_json() Method
import pandas as pd
# Creating Dataframe
df = pd.DataFrame(
[['Stranger Things', 'Money Heist'], ['Most Dangerous Game', 'The Stranger']],
columns=['Netflix', 'Quibi'])
print(df)Output
Netflix Quibi
0 Stranger Things Money Heist
1 Most Dangerous Game The StrangerLet’s convert DataFrame to JSON using the to_json() function.
import pandas as pd
# Creating Dataframe
df = pd.DataFrame(
[['Stranger Things', 'Money Heist'], ['Most Dangerous Game', 'The Stranger']],
columns=['Netflix', 'Quibi'])
data = df.to_json(orient='index')
print(data)Output
{"0":{"Netflix":"Stranger Things","Quibi":"Money Heist"},
"1":{"Netflix":"Most Dangerous Game","Quibi":"The Stranger"}}Example 2: orient = ‘columns’
import pandas as pd
# Creating Dataframe
df = pd.DataFrame(
[['Stranger Things', 'Money Heist'], ['Most Dangerous Game', 'The Stranger']],
columns=['Netflix', 'Quibi'])
data = df.to_json(orient='columns')
print(data)Output
{"Netflix":{"0":"Stranger Things","1":"Most Dangerous Game"},
"Quibi":{"0":"Money Heist","1":"The Stranger"}}Example 3: orient=’table’
import pandas as pd
# Creating Dataframe
df = pd.DataFrame(
[['Stranger Things', 'Money Heist'], ['Most Dangerous Game', 'The Stranger']],
columns=['Netflix', 'Quibi'])
data = df.to_json(orient='table')
print(data)Output
{"schema":{"fields":[{"name":"index","type":"integer"},
{"name":"Netflix","type":"string"},
{"name":"Quibi","type":"string"}],
"primaryKey":["index"],"pandas_version":"1.4.0"},
"data":[{"index":0,"Netflix":"Stranger Things",
"Quibi":"Money Heist"},{"index":1,
"Netflix":"Most Dangerous Game","Quibi":"The Stranger"}]}
Example 4: orient=’ values’
import pandas as pd
# Creating Dataframe
df = pd.DataFrame([['Stranger Things', 'Money Heist'],
['Most Dangerous Game', 'The Stranger']],
columns=['Netflix', 'Quibi'])
# Convert DataFrame to JSON
data = df.to_json(orient='values')
print(data)Output
[["Stranger Things","Money Heist"],["Most Dangerous Game","The Stranger"]]Example 5: orient=’index’
# app.py
import pandas as pd
# Creating Dataframe
df = pd.DataFrame([['Stranger Things', 'Money Heist'],
['Most Dangerous Game', 'The Stranger']],
columns=['Netflix', 'Quibi'])
# Convert DataFrame to JSON
data = df.to_json(orient='index')
print(data)Output
{"0":{"Netflix":"Stranger Things","Quibi":"Money Heist"},
"1":{"Netflix":"Most Dangerous Game","Quibi":"The Stranger"}}Example 6: orient=’records’
import pandas as pd
# Creating Dataframe
df = pd.DataFrame([['Stranger Things', 'Money Heist'],
['Most Dangerous Game', 'The Stranger']],
columns=['Netflix', 'Quibi'])
# Convert DataFrame to JSON
data = df.to_json(orient='records')
print(data)Output
[{"Netflix":"Stranger Things","Quibi":"Money Heist"},
{"Netflix":"Most Dangerous Game","Quibi":"The Stranger"}]Example 7: orient=’split’
import pandas as pd
# Creating Dataframe
df = pd.DataFrame([['Stranger Things', 'Money Heist'],
['Most Dangerous Game', 'The Stranger']],
columns=['Netflix', 'Quibi'])
# Convert DataFrame to JSON
data = df.to_json(orient='split')
print(data)Output
{"columns":["Netflix","Quibi"],"index":[0,1],"data":[["Stranger Things","Money Heist"],
["Most Dangerous Game","The Stranger"]]}That’s it.
Krunal Lathiya is a seasoned Computer Science expert with over eight years in the tech industry. He boasts deep knowledge in Data Science and Machine Learning. Versed in Python, JavaScript, PHP, R, and Golang. Skilled in frameworks like Angular and React and platforms such as Node.js. His expertise spans both front-end and back-end development. His proficiency in the Python language stands as a testament to his versatility and commitment to the craft.
