Inserts rows into a sequence. This overwrites data in rows and columns that exist.
Data posted.
required | Array of Select by Id (object) or Select by ExternalId (object) (SequencePostData) [ 1 .. 1000 ] items |
Empty response.
from cognite.client.data_classes import Sequence, SequenceColumn seq = client.sequences.create(Sequence(columns=[SequenceColumn(value_type="String", external_id="col_a"), SequenceColumn(value_type="Double", external_id ="col_b")])) data = [(1, ['pi',3.14]), (2, ['e',2.72]) ] client.sequences.data.insert(columns=["col_a","col_b"], rows=data, id=1) data = [{"rowNumber": 123, "values": ['str',3]}, {"rowNumber": 456, "values": ["bar",42]} ] client.sequences.data.insert(data, id=1, columns=["col_a","col_b"]) # implicit columns are retrieved from metadata data = {123 : ['str',3], 456 : ['bar',42] } client.sequences.data.insert(columns=['stringColumn','intColumn'], rows=data, id=1) data = client.sequences.data.retrieve(id=2,start=0,end=10) client.sequences.data.insert(rows=data, id=1,columns=None) import pandas as pd df = pd.DataFrame({'col_a': [1, 2, 3], 'col_b': [4, 5, 6]}, index=[1, 2, 3]) client.sequences.data.insert_dataframe(df, id=123) from cognite.client.data_classes import Sequence, SequenceColumn seq = client.sequences.create(Sequence(columns=[SequenceColumn(value_type="String", external_id="col_a"), SequenceColumn(value_type="Double", external_id ="col_b")])) data = [(1, ['pi',3.14]), (2, ['e',2.72]) ] client.sequences.data.insert(columns=["col_a","col_b"], rows=data, id=1) data = [{"rowNumber": 123, "values": ['str',3]}, {"rowNumber": 456, "values": ["bar",42]} ] client.sequences.data.insert(data, id=1, columns=["col_a","col_b"]) # implicit columns are retrieved from metadata data = {123 : ['str',3], 456 : ['bar',42] } client.sequences.data.insert(columns=['stringColumn','intColumn'], rows=data, id=1) data = client.sequences.data.retrieve(id=2,start=0,end=10) client.sequences.data.insert(rows=data, id=1,columns=None) import pandas as pd df = pd.DataFrame({'col_a': [1, 2, 3], 'col_b': [4, 5, 6]}, index=[1, 2, 3]) client.sequences.data.insert_dataframe(df, id=123)
{ }