What is Pandas?
Pandas is a powerful, fast, and open-source library built on NumPy. It is used for data manipulation and real-world data analysis in Python. Easy handling of missing data, Flexible reshaping and pivoting of data sets, and size mutability make pandas a great tool for performing data manipulation and handling the data efficiently.
Data Processing with Pandas
Data Processing is an important part of any task that includes data-driven work. It helps us to provide meaningful insights from the data. As we know Python is a widely used programming language, and there are various libraries and tools available for data processing.
In this article, we are going to see Data Processing in Python, Loading, Printing rows and Columns, Data frame summary, Missing data values Sorting and Merging Data Frames, Applying Functions, and Visualizing Dataframes.
Table of Content
- What is Data Processing in Python?
- What is Pandas?
- Loading Data in Pandas DataFrame
- Printing rows of the Data
- Printing the column names of the DataFrame
- Summary of Data Frame
- Descriptive Statistical Measures of a DataFrame
- Missing Data Handing
- Sorting DataFrame values
- Merge Data Frames
- Apply Function
- By using the lambda operator
- Visualizing DataFrame
- Conclusion