What is Pandas?
Pandas is a Python library used for working with data sets.
It has functions for analyzing, cleaning, exploring, and manipulating data.
The name "Pandas" has a reference to both "Panel Data", and "Python Data Analysis" and was created by Wes McKinney in 2008.
Why Use Pandas?
Pandas allows us to analyze big data and make conclusions based on statistical theories.
Pandas can clean messy data sets, and make them readable and relevant.
Relevant data is very important in data science.
What Can Pandas Do?
Pandas gives you answers about the data. Like:
Pandas are also able to delete rows that are not relevant, or contains wrong values, like empty or NULL values. This is called cleaning the data.
Pandas is mainly used for data analysis and associated manipulation of tabular data in Dataframes. Pandas allows importing data from various file formats such as comma-separated values, JSON, Parquet, SQL database tables or queries, and Microsoft Excel. Pandas allows various data manipulation operations such as merging, reshaping, selecting, as well as data cleaning, and data wrangling features. The development of pandas introduced into Python many comparable features of working with DataFrames that were established in the R programming language. The pandas library is built upon another library NumPy, which is oriented to efficiently working with arrays instead of the features of working on DataFrames.
About the Instructor:
Sharad Khare is Data Intelligence Scientist and Fraud Analyst with 9+ years of Legal experience in the Global Safety and Investigative sectors with content policy, anti-abuse operations, Audit Intellectual Property violations, Anti-Fraud Operations and Investigation.
He is also the External Invitee Faculty of different different Education institutions for tutoring HTML, PHP, R Language, MYSQL, Python, JavaScript and Data science .
