Python basics for data — quiz

Why can a working notebook fail for someone else?

1. Version differences only
2. Cells may have been run out of order
3. Jupyter is unreliable
4. Missing internet

Answer: Cells may have been run out of order — Restart & Run All is the check that catches it.

Which library reads .xlsx files?

1. numpy
2. openpyxl
3. seaborn
4. requests

Answer: openpyxl — pandas needs openpyxl installed to use read_excel.

'10' + '5' returns:

1. 15
2. '105'
3. An error
4. 105

Answer: '105' — String concatenation, not addition. Convert first.

int(3.9) returns:

1. 4
2. 3
3. 3.9
4. An error

Answer: 3 — int() truncates toward zero. round() gives 4.

cities[0:2] on a 4-item list returns:

1. 3 items
2. 2 items
3. 4 items
4. An error

Answer: 2 items — Slices are end-exclusive throughout Python.

In pd.DataFrame({'a': [1,2]}), the key 'a' becomes:

1. A row
2. A column
3. An index
4. A data type

Answer: A column — Dictionary keys become column names.

Why avoid looping over DataFrame rows?

1. It is invalid
2. Vectorised column operations are far faster and clearer
3. Loops cannot access columns
4. It uses more memory only

Answer: Vectorised column operations are far faster and clearer — Often around 100x slower, and less readable.

Python combines conditions with:

1. && and ||
2. and / or / not
3. AND / OR
4. + and -

Answer: and / or / not — The word forms are the Python syntax.