Скачать или смотреть 5 Excel Shortcuts to Format Data Faster! 🎨⚡

Ctrl + 1

Opens the Format Cells dialog box, where you can customize number formats, alignment, borders, fonts, and more.

Ctrl + B

Toggles Bold formatting on the selected text or cell values—great for highlighting headers or key figures.

Ctrl + I

Toggles Italic formatting, useful for emphasizing notes, subheaders, or specific text within cells.

Ctrl + U

Toggles Underline formatting on the selected text—commonly used for emphasis or to mark totals.

Alt + E → S → V

Opens the Paste Special → Values command, pasting only the values (without formulas or formatting) from the copied data.

Interview Questions & Answers

1. Which shortcut opens the Format Cells dialog box?

– Answer: Ctrl + 1

2. How do you quickly make text bold in Excel?

– Answer: Ctrl + B

3. What is the shortcut to italicize cell contents?

– Answer: Ctrl + I

4. Which keys underline text in Excel?

– Answer: Ctrl + U

5. How do you paste only values without formatting or formulas?

– Answer: Alt + E → S → V
import numpy as np
arr = np.arange(8)
reshaped = arr.reshape(2, 2, 2)

One-liner
reshaped = __import__('numpy').arange(8).reshape(2,2,2)


Here, a 1D array of 8 elements becomes a 3D array with shape (2, 2, 2).

5 Interview Questions (with Answers):

Q: What is the difference between reshape() and resize() in NumPy?
A: reshape() changes shape without modifying data size, while resize() can change both shape and size (filling gaps if needed).

Q: What does -1 mean in reshape()?
A: It lets NumPy automatically calculate the missing dimension based on the array’s size.

Q: What’s the difference between .ravel() and .flatten()?
A: .ravel() often returns a view (faster), while .flatten() always returns a copy.

Q: Can reshaping change the order of elements?
A: No, reshaping rearranges elements in row-major (C-style) or column-major (Fortran-style) order but doesn’t shuffle values.

Q: Why is reshaping important in machine learning?
A: It prepares data into the correct shape for models (e.g., converting 1D data into 2D matrices or reshaping images into 4D tensors).

#numpy #Python #DataScience #MachineLearning #Reshape #CodingTips #InterviewPrep