Python Pandas Overview

Pandas is a high-level data manipulation tool for Python, offering data structures and operations for manipulating numerical tables and time series.

Core Data Structures

Pandas provide two central data structures for manipulating data: Series and DataFrames.

A one-dimensional array-like object that can hold any data type.

A two-dimensional, size-mutable, and potentially heterogeneous tabular data structure.

Previously, panels represented three-dimensional data, now replaced by MultiIndex DataFrames.

Pandas supports various file formats for data exchange.

Importing and exporting data in comma-separated values files.

Integration with Excel files for reading and writing spreadsheet data.

Interaction with SQL databases to load and save data.

Parsing JSON formatted data into DataFrames.

Several methods and functionalities to clean and transform data.

Selecting particular rows and columns based on conditions.

Combining data from different DataFrames based on a common key.

Aggregating data based on categories.

Reshaping data by summarizing and reorganizing it.

Pandas provide tools for deep analysis.

Calculating descriptive statistics for insights.

Generating plots and charts directly from data.

Handling date and time indexed data for trends and seasonality.

Detecting and imputing missing data for consistency.