Detailed explanation about python pandas library

Explanation about python pandas library

1. Introduction to the pandas Library in Python Data Manipulation and Analysis Your Name Date

2. Introduction - What is pandas? - An open-source data analysis and manipulation library for Python - Provides data structures and functions needed to work with structured data seamlessly

3. Installation - Using pip: ```bash pip install pandas ``` - Using conda: ```bash conda install pandas ```

4. Core Data Structures - Series: One-dimensional labeled array Example: ```python import pandas as pd s = pd.Series([1, 3, 5, 7, 9]) ``` - DataFrame: Two-dimensional labeled data structure Example: ```python data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35]} df = pd.DataFrame(data) ```

5. Reading Data - Reading CSV Files: ```python df = pd.read_csv('data.csv') ``` - Reading Excel Files: ```python df = pd.read_excel('data.xlsx') ```

6. Data Inspection - Viewing the first few rows: ```python df.head() ``` - Viewing DataFrame info: ```python df.info() ```

7. Data Manipulation - Handling missing values: ```python df.dropna() df.fillna(value) ``` - Applying functions: ```python df.apply(np.sqrt) ```

8. Grouping and Aggregating - Grouping data: ```python grouped = df.groupby('column_name') ``` - Aggregating data: ```python grouped.mean() ```