Machine Learning Challenge: Day 4

Using Pandas to Get Familiar with Your Data



Pandas is a powerful and flexible open-source data manipulation and analysis library for the Python programming language. It provides data structures such as DataFrame and Series, which are designed to work with large and complex datasets. By using pandas, you can easily get familiar with your data by performing tasks such as:

  • Loading data from various file formats (e.g. CSV, Excel, JSON)
  • Exploring and summarizing your data (e.g. head, tail, describe)
  • Cleaning and transforming your data (e.g. filling in missing values, converting data types)
  • Filtering and selecting specific rows and columns
  • Grouping and aggregating your data
  • Sorting and ordering your data
  • Merging and joining multiple datasets

One of the most important features of pandas its ability to handle missing data. It provides various methods to handle missing data, such as filling missing values with a specific value or using interpolation techniques.

Overall, pandas is a great tool for data exploration and manipulation, and it's widely used by data scientists and analysts in various industries.

Find the Dataset for this notebook from here

  • Practice for Day-4 

 


data-cleaning-challenge-handling-missing-values

Comments

Popular posts from this blog

Roadmap for 30 Day Machine Learning Challange

Machine Learning Challenge: Day 3

Machine Learning Challenge: Day 6