How to iterate over rows of a Frame in DataTable

Question

With pandas I usually iterate the rows of a DataFrame with itertuples or iterrows. How can I do this kind of iteration on a Frame from Python DataTable?

Exemple of Pandas iteration that I need:

for row in df_.itertuples():
    print(row)

Asked By: Danilo Matrangolo Marano

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Source

Answer 1

From the documentation for DataTables:

A Frame is column-oriented in the sense that internally the data is stored separately for each column. Each column has its own name and type. Types may be different for different columns but cannot vary within each column.

That being said, you can iterate over rows as:

from datatable import dt, f, by, g, join, sort, update, ifelse

data = {"A": [1, 2, 3, 4, 5],
        "B": [4, 5, 6, 7, 8],
        "C": [7, 8, 9, 10, 11],
        "D": [5, 7, 2, 9, -1]}

# datatable
DT = dt.Frame(data)

# select single row
print(DT[2, :])

# Select several rows by their indices
print(DT[[2,3,4], :])

# Select a slice of rows by position
print(DT[2:5, :])

# Select rows on multiple conditions, using OR
print(DT[(f.A>3) | (f.B<5), :])

For more row iteration examples and comparison with Pandas DataFrame, have a look at this official page. In case you have some issues, you may raise the issue over at DataTable official github repo.

Answered By: anurag

Answer 2

You can use .to_tuples to achieve row iteration.

from datatable import dt, f, by, g, join, sort, update, ifelse
data = {"A": [1, 2, 3, 4, 5],
        "B": [4, 5, 6, 7, 8],
        "C": [7, 8, 9, 10, 11],
        "D": [5, 7, 2, 9, -1]}

DT = dt.Frame(data)

for row in DT.to_tuples():
        print(row)

Answered By: 彭俊文

How to iterate over rows of a Frame in DataTable

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