Demo Pull Request

[owen-connor]

No description provided.

[gitnotebooks]

Found 2 changed notebooks. Review the changes at https://app.gitnotebooks.com/GitNotebooks/demo/pull/4

[smith-kyle]

LGTM

[smith-kyle]

hi i am comment

[smith-kyle]

Comment

[smith-kyle]

hey don't do this

[smith-kyle]

One of the essential pieces of NumPy is the ability to perform quick element-wise operations, both with basic arithmetic (addition, subtraction, multiplication, etc.) and with more sophisticated operations (trigonometric functions, exponential and logarithmic functions, etc.).

test comment

[smith-kyle]

my reply in github

[smith-kyle]

done-zo

[smith-kyle]

One of the essential pieces of NumPy is the ability to perform quick element-wise operations, both with basic arithmetic (addition, subtraction, multiplication, etc.) and with more sophisticated operations (trigonometric functions, exponential and logarithmic functions, etc.).

new review comment

[smith-kyle]

my gh reply

[smith-kyle]

        raise ValueError("Division by zero is not allowed")


def modulus(a, b):

how

[smith-kyle]

# Operating on Data in Pandas

Hey @owen-connor I'm going to ping you for a demo

[smith-kyle]

My review is done

[smith-kyle]

Copied from [https://github.com/jakevdp/PythonDataScienceHandbook](https://github.com/jakevdp/PythonDataScienceHandbook) with modifications to demonstrate notebook diffing.

here's my review comment

[smith-kyle]

fill = A.stack().sum()
A.add(B, fill_value=fill)

Looks good

[smith-kyle]

    return a * b


def divide(a, b):
    if b != 0:
        return a / b
    else:
        raise ValueError("Division by zero is not allowed")

another comment

[smith-kyle]

A = pd.DataFrame(rng.randint(0, 20, (2, 2)),
                 columns=list('AB'))
B = pd.DataFrame(rng.randint(0, 10, (3, 3)),

test

[owen-connor]

Suggested change

	"A = rng.randint(10, size=(4, 4))\n",