Evaluate your data python
When you get data from you, you are right that we are listed in the list. As is the serials that can be evaluated and processed in a stronger manre.
Here is an example of how to refund the data from JSON responds using Python:
by assuming that JSON Answer
`Json
We started
{
ID: 1,
Name: John Doe,
Age: 30,
"City": "New York"
},
{
ID: 2,
Name: Jane Smith,
Age: 25,
City: Los Angeles.
}
]
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The use of Python to analyze and return data
Python
Import JSON
By assuming
data =
{"S": 1, "Name": "John Doe", Age: 30, "City": "New York"},
{"S": 2, "Name": "Jane Smith", Age: 25, City: "Los Angeles"}
]
Define a feature to extract the data
Def get_data (data):
Keys_to_Extract = ["S", "Name", "Age"]
For element data:
Exted_info = {}
KEY_TO_Extract:
If the item key:
Exted_info [Key] = Item [key]
excitement_info
Example
For a person get_data (data):
Print (a person)
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In this example, the lack of well -being getstaa is able to perform your objects ("data") and pay for the generator's expressiveness containing data (eg "name" and "age"). We use the "Example Usage" section to repeat the pulled data.
Access to specific data *
To achieve specific data, you can simply repeat the generator's expression:
Python
For a person get_data (data):
Print (Person ["S"]
Print: 1
Print (Person ["Name"])
Print: John Doe
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Or, if you want to use the Coop Instance Core, you will define a separate point in the data as an argument:
Python
Def Get_person (Person):
Back {"S": Person ["ID"], "Name": Person ["Name"]}
Example
data =
{"S": 1, "Name": "John Doe", Age: 30, "City": "New York"},
{"S": 2, "Name": "Jane Smith", Age: 25, City: "Los Angeles"}
]
Personal data:
Print (get_person (person))
` Re
This approach is more sadness when a larger set of data that does not fit into memory.