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Python Variables: How to Define/Declare String Variable Types

What is a Variable in Python?
A Python variable is a reserved memory location to store values. In other words, a variable in a python program gives data to the computer for processing.

Python Variable Types
Every value in Python has a datatype. Different data types in Python are Numbers, List, Tuple, Strings, Dictionary, etc. Variables in Python can be declared by any name or even alphabets like a, aa, abc, etc.

How to Declare and use a Variable
Let see an example. We will define variable in Python and declare it as “a” and print it.

1 a=100
2 print (a)

Python Data Science Handbook

Python Data Science Handbook: full text in Jupyter Notebooks. This repository contains the entire Python Data Science Handbook, in the form of (free!) Jupyter notebooks.

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Essential NumPy Functions for Data Analysis

Array Creation:

np.array() - Create an array from a list.

np.zeros((rows, cols)) - Create an array filled with zeros.

np.ones((rows, cols)) - Create an array filled with ones.

np.arange(start, stop, step) - Create an array with a range of values.


Array Operations:

np.sum(array) - Calculate the sum of array elements.

np.mean(array) - Compute the mean.

np.median(array) - Calculate the median.

np.std(array) - Compute the standard deviation.


Indexing and Slicing:

array[start:stop] - Slice an array.

array[row, col] - Access a specific element.

array[:, col] - Select all rows for a column.


Reshaping and Transposing:

array.reshape(new_shape) - Reshape an array.

array.T - Transpose an array.


Random Sampling:

np.random.rand(rows, cols) - Generate random numbers in [0, 1).

np.random.randint(low, high, size) - Generate random integers.


Mathematical Operations:

np.dot(A, B) - Compute the dot product.

np.linalg.inv(A) - Compute the inverse of a matrix.

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Roadmap to become a Python Developer:

📂 Learn Python Basics (Syntax, Data Types, Loops)
∟📂 Learn Data Structures (Lists, Tuples, Dicts, Sets)
∟📂 Learn Functions & Modules
∟📂 Learn File Handling & Exceptions
∟📂 Learn OOP Concepts
∟📂 Learn Libraries (Pandas, NumPy, etc.)
∟📂 Learn Web Development (Flask / Django)
∟📂 Learn APIs & Database Integration
∟📂 Build Projects & Portfolio
∟✅ Apply for Job

React ❤️ for More

9 tips to improve your code:

- Declare variables close to usage
- Functions do 1 thing
- Avoid long functions
- Avoid long lines
- Don't repeat code
- Use descriptive variable/function names
- Use few arguments
- Simplify conditions (return age >17;)
- Remove unused code

Without errors, No-one can become a good programmer.
Errors are the most important phase of learning to code.

What are the common built-in data types in Python?

Python supports the below-mentioned built-in data types:

Immutable data types:

👉Number
👉String
👉Tuple

Mutable data types:

👉List
👉Dictionary
👉set

Python Most Important Interview Questions

Question 1: Calculate the average stock price for Company X over the last 6 months.

Question 2: Identify the month with the highest total sales for Company Y using their monthly sales data.

Question 3: Find the maximum and minimum stock price for Company Z on any given day in the last year.

Question 4: Create a column in the DataFrame showing the percentage change in stock price from the previous day for Company X.

Question 5: Determine the number of days when the stock price of Company Y was above its 30-day moving average. Question

6: Compare the average stock price of Companies X and Z in the first quarter of the year.

#Data#
----------------------------------------------
import pandas as pd
data = {   'Date': pd.date_range(start='2023-01-01', periods=180, freq='D'),   'CompanyX_StockPrice': pd.np.random.randint(50, 150, 180),   'CompanyY_Sales': pd.np.random.randint(20000, 50000, 180),   'CompanyZ_StockPrice': pd.np.random.randint(70, 200, 180) }

df = pd.DataFrame(data)

⌨️ Calculate derivatives in Python

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