Pandas for Data Analysis in Python

Published 06/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 16 lectures (1h 19m) | Size: 612.5 MB

Data Analysis with Pandas and Python. Beginners are welcome!

What you’ll learn
Data analysis using python
Importing and creating data frame in python
Data cleaning
Correlations

Requirements
There are no prerequisites for this course but basic knowledge of python is a plus.

Description

Welcome to the most comprehensive Pandas course available on Udemy! An excellent choice for both beginners and experts looking to expand their knowledge on one of the most popular Python libraries in the world!

Pandas for Data Analysis in Python offers in-depth video tutorials on the most powerful data analysis toolkit

Why learn pandas?

If you’ve spent time in a spreadsheet software like MS Excel or Google Sheets and want to take your data analysis skills to the next level, this course is for you!

Pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real-world data analysis in Python.

Pandas is the most powerful and flexible open source data analysis/manipulation tool available in any language.

pandas is well suited for many different kinds of data

Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet

Ordered and unordered (not necessarily fixed-frequency) time series data.

Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels

Any other form of observational / statistical data sets. The data need not be labeled at all to be placed into a pandas data structure

Data Analysis with Pandas and Python is bundled with dozens of datasets for you to use. Dive right in and follow along with my lessons to see how easy it is to get started with pandas!
Who this course is for
Students and professionals who wants to do data analysis using python.
Python developer who wants to do analysis of tabular data.


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