# Select multiple columns in Python Pandas

**URL:** https://sentry.io/answers/select-multiple-columns-in-python-pandas/

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## The Problem

How do I select multiple columns from an existing DataFrame and create a new DataFrame with them?

## The Solution

We can do this by creating a list of the column names we want and passing them to the [DataFrame constructor method](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html), along with the original DataFrame. The code below shows an example:

```python
import pandas

# Our main DataFrame
main = pandas.DataFrame([["apple", 1, 2], ["orange", 3, 4], ["pear", 5, 6]],
                        columns=["product", "cost_price", "sale_price"])
print(main)
print("\n")

# Our smaller DataFrame
subset = pandas.DataFrame(main, columns=["product", "sale_price"])
print(subset)
```

This code will produce the following output:

```
  product  cost_price  sale_price
0   apple           1           2
1  orange           3           4
2    pear           5           6

  product  sale_price
0   apple           2
1  orange           4
2    pear           6
```

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*Source: [sentry.io/answers/select-multiple-columns-in-python-pandas/](https://sentry.io/answers/select-multiple-columns-in-python-pandas/)*