Pandas: Data Analysis and Manipulation in Python
Pandas is a Python library that provides powerful data analysis and manipulation capabilities. It is widely used in the fields of data science, machine learning, and finance. In this post, we will explore the basics of Pandas and its key features. Data Structures in Pandas Pandas provides two primary data structures: Series and DataFrame . A Series is a one-dimensional labeled array that can hold any data type. A DataFrame is a two-dimensional labeled data structure with columns of potentially different types. Here are some examples: import pandas as pd # create a Series my_series = pd.Series([1, 2, 3, 4, 5]) print(my_series) create a DataFrame my_data = {'name': ['John', 'Mary', 'Alex', 'Jane'], 'age': [25, 32, 18, 47]} my_dataframe = pd.DataFrame(my_data) print(my_dataframe) In this example, we import the Pandas library and create a Series of integers and a DataFrame of names and ages. We then print out the Series and...