What is a DataFrame | Pandas | Pandas Tutorial | Pandas Data Structure DataFrame

A DataFrame in Python is a two-dimensional, size-mutable, tabular data structure with labeled axes (rows and columns). It is one of the core data structures in the Pandas library, which is a popular data analysis and manipulation tool in Python.

A DataFrame can be thought of as a table, where each column represents a variable, and each row represents an observation. The columns in a DataFrame can have different data types, such as integers, floats, strings, booleans, or other objects. Each column in a DataFrame is represented as a Pandas Series, which is a one-dimensional labeled array capable of holding any data type.

In a DataFrame, the rows and columns can be labeled with descriptive names or integers. The row labels are called the index, while the column labels are called the column headers. You can access, manipulate, and transform the data in a DataFrame using various methods and functions provided by the Pandas library.

Here's an example of a simple DataFrame in Python:

Name Age City
0 John 28 Paris
1 Jane 32 Tokyo
2 Bob 45 Rome
3 Mary 27 Dubai
In this example, we have a DataFrame with four rows and three columns ('Name', 'Age', and 'City'). The index is represented by integers 0, 1, 2, and 3. Each column contains data of a different data type, where 'Name' and 'City' are strings, and 'Age' is an integer.

Data frame is a 2 dimensional labeled data structure with column that can hold any data type.

you can create a data frame using following
- calling a data frame function and passing data.
a python dictionary of one dimensional array, list , dictionary or series.
a multidimensional numpy array.
a series or another data frame.

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