Ashish Chandan Dictionaries are collections of key-value pairs. Each key in a dictionary is unique and maps to a value. Dictionaries are created using curly braces {} or the dict() function. # Creating a dictionary of names and ages my_dict = {“Alice”: 25, “Bob”: 30, “Charlie”: 35} # Creating a dictionary of stock prices stock_prices = {“AAPL”: … Read more
Sets are unordered collections of unique elements. Sets are created using curly braces {} or the set() function. # Creating a set of integers my_set = {1, 2, 3, 4, 5} # Creating a set of strings my_strings = set([“apple”, “banana”, “cherry”]) Sets support mathematical set operations such as union, intersection, and difference. # Set … Read more
Tuples are similar to lists, but they are immutable, which means their elements cannot be changed. Tuples are created using parentheses (). # Creating a tuple of integers my_tuple = (1, 2, 3, 4, 5) # Creating a tuple of strings my_strings = (“apple”, “banana”, “cherry”) Tuples can be accessed and sliced in the … Read more
Lists Lists are one of the most commonly used data structures in Python. A list is an ordered collection of elements, which can be of any type, such as integers, floats, strings, or other objects. Lists are created using square brackets [] and elements are separated by commas. # Creating a list of integers my_list … Read more
Matplotlib is a popular data visualization library in Python, which is widely used in Data Engineering to plot and analyze data. With Matplotlib, you can create a wide range of charts and graphs including line charts, bar charts, scatter plots, histograms, and more. Here are some common use cases of Matplotlib in Data Engineering: Visualizing … Read more
NumPy is a powerful library for numerical computing in Python. It provides a high-performance array object, which can be used for storing and manipulating large arrays of numerical data. NumPy provides a wide range of functions for performing mathematical operations on arrays, including linear algebra, Fourier transforms, and more. NumPy also provides functions for reading … Read more
Pandas is a popular library for data analysis and manipulation in Python. It provides data structures for efficiently storing and manipulating large datasets, including support for handling missing data, merging datasets, and reshaping data. Pandas provides a wide range of data manipulation functions, including filtering, grouping, aggregation, and more. Pandas also provides functions for reading … Read more
Photo by charlesdeluvio on Unsplash Python is one of the most popular programming languages in use today. Developed in the late 1980s by Guido van Rossum, Python has become one of the most widely used languages in the world. Known for its simple syntax and ease of use, Python has become a go-to language for beginners and … Read more
