python pandas dataframe methods

Pandas is a powerful data manipulation library in Python, and the DataFrame is one of its key data structures. It provides a two-dimensional labeled data structure with columns that can be of different types. In this tutorial, we'll explore various methods available for manipulating and analyzing data using Pandas DataFrame.
Make sure you have Pandas installed before you start. You can install it using:
Let's start by creating a simple DataFrame:
This will output:
These methods allow you to view the first and last rows of the DataFrame:
Provides descriptive statistics of the DataFrame:
Displays a concise summary of the DataFrame, including data types and memory usage:
Returns the dimensions of the DataFrame (rows, columns):
Returns the column labels of the DataFrame:
Used for accessing a group of rows and columns by label(s) or a boolean array:
Set and reset the DataFrame index:
Sorts the DataFrame by specified columns:
Group DataFrame by a column and perform aggregate functions:
Merge two DataFrames based on a common column:
These are just a few of the many methods available in Pandas for working with DataFrames. The library is rich in functionality, making it a powerful tool for data manipulation and analysis in Python. Explore the official documentation for more details and options: Pandas Documentation.
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