What is Data Frame ?

A DataFrame is a two-dimensional, size-mutable, and potentially heterogeneous tabular data structure. In simple terms, it’s like a table or spreadsheet where you can store rows and columns of data. Each column can have different data types such as integers, floats, and strings.

In Python, DataFrames are a powerful way to store and work with tabular data (like data in a table or spreadsheet). You can think of a DataFrame as a table where each column is a different data type (numbers, text, etc.), and each row represents a record or an entry in the dataset.

•   Rows represent individual data points (observations or records).
•   Columns represent variables (attributes or features) of those records.

 

DataFrames are a part of the Pandas library, which is a popular tool for data analysis.

 CREATING DATAFRAMES

 

 1.Reading Data into DataFrames:

pip install pandas

import pandas as pd

# Reading a CSV file into a DataFrame

df = pd.read_csv(‘data.csv’)

# Displaying the first few rows of the DataFrame

print(df.head())

 Output: The data will be extracted from CSV file and shown

 2.Creating a DataFrame from a Dictionary:

Taking example of students and their marks

 import pandas as pd

# Data in the form of a dictionary

data = {

               ‘Name’: [‘Alice’, ‘Bob’, ‘Charlie’],

                 ‘Age’: [20, 21, 22],

                 ‘Score’: [85, 90, 88]

                 }

# Creating a DataFrame

df = pd.DataFrame(data)

 # Printing the DataFrame

print(df)

 output:

    Name    Age  Score

0  Alice      20      85

1   Bob        21      90

2  Charlie  22      88

 3.Creating a DataFrame from a List of Lists:

 data = [

[‘Alice’, 20, 85],

[‘Bob’, 21, 90],

[‘Charlie’, 22, 88]

]

columns = [‘Name’, ‘Age’, ‘Score’]

df = pd.DataFrame(data, columns=columns)

print(df)

 

Output:

     Name    Age   Score

0   Alice     20        85

1    Bob       21         90

2   Charlie  22        88

 Axis in Pandas DataFrame:

In Pandas, axis is a parameter used in many functions to specify whether the operation should be applied to rows (axis=0) or columns (axis=1).

• Axis 0 refers to the rows (vertical axis).
• Axis 1 refers to the columns (horizontal axis).

 Index in DataFrames:

In a DataFrame, an index refers to the labels that are assigned to the rows. It helps uniquely identify each row in the DataFrame, allowing for easy and efficient access, selection, and manipulation of data. The index serves as the row label and is crucial for various operations like filtering, sorting, and joining DataFrames.