construct_from_dataframe()
This operation creates a collection with the specified dataframe.
Request Syntax
construct_from_dataframe(
name: str,
primary_field: str,
dataframe: pandas.DataFrame
)
PARAMETERS:
name (string) -
[REQUIRED]
The name of the collection to create.
primary_field (string) -
[REQUIRED]
The name of the primary field. It should be one of the column labels in the following dataframe.
dataframe (pandas.DataFrame)
[REQUIRED]
The dataframe containing the data to be inserted into the collection.
You can form a data frame in any way, as demonstrated in the Example section on this page.
dataframe = pd.DataFrame({ "id": [5,6,7,8,9], "vector": [ [0.1,0.2,-0.3,-0.4,0.5], [0.3,-0.1,-0.2,-0.6,0.7], [-0.6,-0.3,0.2,0.8,0.7], [0.6,0.2,-0.3,-0.8,0.5], [0.3,0.1,-0.2,-0.6,-0.7], ] })
RETURN TYPE:
tuple (Collection, MutationResults)
RETURNS:
A tuple containing the collection and a MutationResult object returned by the insert() operation.
A MutationResult object contains the following fields:
insert_count (int)
The count of inserted entities.
delete_count (int)
The count of deleted entities.
upsert_count (int)
The count of upserted entities.
succ_count (int)
The count of successful executions during this operation.
succ_index (list)
A list of index numbers starting from 0, each indicating a successful operation.
err_count (int)
The count of failed executions during this operation.
err_index (list)
A list of index numbers starting from 0, each indicating a failed operation.
primary_keys (list)
A list of primary keys for the inserted entities.
timestamp (int)
The timestamp at which this operation is completed.
EXCEPTIONS:
SchemaNotReadyException
This exception will be raised when the specified primary field is not valid.
Examples
import pandas as pd
from pymilvus import Collection
collection, results = Collection.construct_from_dataframe(
name="test_collection",
primary_field="id",
dataframe=pd.DataFrame({
"id": [0,1,2,3,4],
"vector": [
[0.1,0.2,-0.3,-0.4,0.5],
[0.3,-0.1,-0.2,-0.6,0.7],
[-0.6,-0.3,0.2,0.8,0.7],
[0.6,0.2,-0.3,-0.8,0.5],
[0.3,0.1,-0.2,-0.6,-0.7],
]
}),
)
Related operations
The following operations are related to construct_from_dataframe():