CODEWITHSUNDEEP
pythonpython-polars
Felix.B
Felix.B

Reputation: 687

How to add a column to a polars DataFrame using .with_columns()

I am currently creating a new column in a polars data frame using

predictions = [10, 20, 30, 40, 50]
df['predictions'] = predictions

where predictions is a numpy array or list containing values I computed with another tool.

However, polars throws a warning, that this option will be deprecated. How can the same result be achieved using .with_columns()?

Upvotes: 26

Views: 24340

Answers (2)

Henry Harbeck
Henry Harbeck

Reputation: 1138

You can now also pass numpy arrays in directly. E.g,

df = pl.DataFrame({"x": [0, 1, 2, 3, 4]})
p1 = [10, 20, 30, 40, 50]
p2 = np.array(p1)
df.with_columns(
    p1=pl.Series(p1), # For python lists, construct a Series
    p2=p2, # For numpy arrays, you can pass them directly
)
# shape: (5, 3)
# ┌─────┬─────┬─────┐
# │ x   ┆ p1  ┆ p2  │
# │ --- ┆ --- ┆ --- │
# │ i64 ┆ i64 ┆ i64 │
# ╞═════╪═════╪═════╡
# │ 0   ┆ 10  ┆ 10  │
# │ 1   ┆ 20  ┆ 20  │
# │ 2   ┆ 30  ┆ 30  │
# │ 3   ┆ 40  ┆ 40  │
# │ 4   ┆ 50  ┆ 50  │
# └─────┴─────┴─────┘

Upvotes: 4

Felix.B
Felix.B

Reputation: 687

The values in the numpy array or list predictions can be add to a polars table using:

predictions = [10, 20, 30, 40, 50]
df.with_columns(pl.Series(name="predictions", values=predictions))

Upvotes: 38

Related Questions