#data_question
Use `normal` to generate normally distributed steps with some mean and standard deviation.

hint: edit your `steps` filter from the preceding question, with 5000 walks at 1000 steps each, to resemble this array
```
steps = np.random.normal(loc = 0, scale = 0.25, size = (nwalks, nsteps))
```

#data_question

Given:
```
arr = np.random.randn(4, 4)
```

Replace only positive values with 2 but do nothing with negative values.

Use `np.where` and return the array if the value is not positive.

#data_question

Using NumPy:

Create a 3 x 6 array of `ones`

Create a 10 x 1 array of `zeroes`

Create a 2 x 3 x 2 `empty` array

Create an array-valued range of 15 integers

read returns a certain number of characters from the file.

The read method advances the file handle’s position by the number of bytes read.

> f.read(int(some_num_bytes))

tell gives you the current position

> f.tell()

If 10 characters is read from the file, the position would be 11 because it took that many bytes to decode 10 characters using the default encoding. You can check the default encoding in the sys module

#data_question

Import the sys module and run

> sys.getdefaultencoding()

You can control the amount of context shown using the %xmode magic command, from Plain (same as the standard Python interpreter) to Verbose (which inlines function argument values and more).

you can step into the stack (using the %debug or %pdb magics) after an error has occurred for interactive post-mortem debugging.

#data_question

Write a function to cast an input as a float with error handling for type and value. If it is a TypeError, return the input as a string.

Currying is computer science jargon (named after the mathematician Haskell Curry) that means deriving new functions from existing ones by partial argument application.

Having a consistent way to iterate over sequences, like objects in a list or lines in a file, is an important Python feature. This is accomplished by means of the iterator protocol, a generic way to make objects iterable. For example, iterating over a dict yields the dict keys. (Image 6)

#data_question ️

What is happening?

Given:

> def remove_punctuation(value):
> ... return re.sub('[!#?]', '', value)

You can use functions as arguments to other functions like the built-in map function, which applies a function to a sequence of some kind.

> for state in map(remove_punctuation, states):
> ... print(state)

#data_question

In your own words, what is happening in the loop?

#data_question

Given https://mastodon.social/@drmorrisj/114336973556278952
and its reply
https://mastodon.social/@drmorrisj/114336978172526096 :

What makes image a bad pseudocode?

Compare it to the prior example and express your answer in your own words.

#data_question

Suppose we have a list of lists containing some English and Spanish names. (Image 7)

You might have gotten these names from a couple of files and decided to organize them by language.

Now, suppose we wanted to get a single list containing all names with two or more e’s in them

Write a for loop to accomplish this task. Be mindful of computation speed

#data_question ️

You can actually wrap this whole operation up in a single nested list comprehension. What would it look like?

#data_question

Given:

> words = ['apple', 'bat', 'bar', 'atom', 'book']

> by_letter ={}

What is the output for image 2?

The setdefault dict method lets you rewrite image 2 as image 3.

#data_question

Given seq1 and seq2 from Image 7 here: https://mastodon.social/@drmorrisj/114314342855860511

What is the result of image 9?

What is the order of evaluation?

#data_question ️

Which is the faster code block in image 10?

insert is computationally expensive compared with append because references to subsequent elements have to be shifted internally to make room for the new element. If you need to insert elements at both the beginning and end of a sequence, you may wish to explore collections.deque, a double-ended queue, for this purpose.

The inverse operation to insert is pop, which removes and returns an element at a particular index.

#data_question

What is the result:

> my_list.pop()

> my_list = ['foo']

Elements can be appended to the end of the list with the append method.

> my_list.append('baz')

Using insert, you can insert an element at a specific location in the list.

> my_list.insert(1, 'bar')

#data_question

In common terms, what did that insert command do?

#data_question ️

Given:

> a = 'foo'
> b = 'bar'

1. Swap the values of the two variables.
2. Swap the values of the two variables in one line.