JSON
In [1]:
# Writing a DataFrame to a JSON File
import pandas as pd
data = {
'Name': ['Alice', 'Bob', 'Charlie'],
'Age': [25, 30, 35],
'City': ['New York', 'Los Angeles', 'Chicago']
}
df = pd.DataFrame(data)
df.to_json('sample1.json', orient='records')
print(df)
Name Age City 0 Alice 25 New York 1 Bob 30 Los Angeles 2 Charlie 35 Chicago
In [2]:
# Writing a DataFrame to a JSON File with Different Orientations
import pandas as pd
data = {
'Name': ['Alice', 'Bob', 'Charlie'],
'Age': [25, 30, 35],
'City': ['New York', 'Los Angeles', 'Chicago']
}
df = pd.DataFrame(data)
df.to_json('sample2_records.json', orient='records')
df.to_json('sample2_split.json', orient='split')
df.to_json('sample2_index.json', orient='index')
df.to_json('sample2_columns.json', orient='columns')
df.to_json('sample2_values.json', orient='values')
print(df)
Name Age City 0 Alice 25 New York 1 Bob 30 Los Angeles 2 Charlie 35 Chicago
In [3]:
# Writing a DataFrame to a JSON File with Indentation
import pandas as pd
data = {
'Name': ['Alice', 'Bob', 'Charlie'],
'Age': [25, 30, 35],
'City': ['New York', 'Los Angeles', 'Chicago']
}
df = pd.DataFrame(data)
df.to_json('sample3.json', orient='records', indent=4)
print(df)
Name Age City 0 Alice 25 New York 1 Bob 30 Los Angeles 2 Charlie 35 Chicago
In [4]:
# Writing a DataFrame to a JSON File with Compression
import pandas as pd
data = {
'Name': ['Alice', 'Bob', 'Charlie'],
'Age': [25, 30, 35],
'City': ['New York', 'Los Angeles', 'Chicago']
}
df = pd.DataFrame(data)
df.to_json('sample4.json.gz', orient='records', lines=True, compression='gzip')
print(df)
Name Age City 0 Alice 25 New York 1 Bob 30 Los Angeles 2 Charlie 35 Chicago
In [5]:
# Reading JSON from a File
import pandas as pd
df = pd.read_json('sample1.json')
print(df)
Name Age City 0 Alice 25 New York 1 Bob 30 Los Angeles 2 Charlie 35 Chicago
In [6]:
# Reading JSON from a String
import pandas as pd
import json
import io
json_str = io.StringIO(u'[{"name": "John", "age": 30, "city": "New York"},{"name": "Anna", "age": 22, "city": "London"},{"name": "Mike", "age": 32, "city": "San Francisco"}]')
df = pd.read_json(json_str)
print(df)
name age city 0 John 30 New York 1 Anna 22 London 2 Mike 32 San Francisco
In [7]:
# Reading Nested JSON
import pandas as pd
nested_json = io.StringIO(u'{"students": [{"name": "John", "age": 30, "city": "New York"},{"name": "Anna", "age": 22, "city": "London"},{"name": "Mike", "age": 32, "city": "San Francisco"}]}')
df = pd.json_normalize(pd.read_json(nested_json)['students'])
print(df)
name age city 0 John 30 New York 1 Anna 22 London 2 Mike 32 San Francisco
In [8]:
# Reading JSON from a URL
import pandas as pd
#url = 'https://api.example.com/data.json'
url="sample3.json"
df = pd.read_json(url)
print(df)
Name Age City 0 Alice 25 New York 1 Bob 30 Los Angeles 2 Charlie 35 Chicago