#2 : How to read CSV file in PYTHON ?? | Working with Series & DataFrame in Pandas | iloc vs loc
"How do you read a CSV file in Python??"
In this video we shall work with
* Interactive Google Colab Environment for Machine Learning and Data Science
* We shall work with 2 data structures in Pandas: Series and DataFrame
* reading a CSV file in Python using Pandas
Watch the video on how to make best use of this tutorial (Lecture 01a): • Pandas #1: structure of PANDAS Python...
"Python and Data Science are the most in-demand skills of 2022"
pandas library in python provides capabilities in
* data processing
* data wrangling
* data analysis
It is also one of the favorite interview topics for interviewers in python for data science machine learning
** Now you could too master this skill. Learn from the basics of pandas using google colab and go all the way to advanced in just 7 days
In this tutorial we shall learn
* data structures in Pandas
* attribute level functionalities
* table level functions
* multiindexing
* important interview questions
Video Overview
00:00 - Introduction
00:13 - google colab
01:32 - series and data frame pandas data structure
07:00 - indexing using iloc and loc
11:18 - copy dataframe
12:35 - reading a csv file
14:09 - bonus section
15:22 - interview questions
The entire tutorial is divided into 5 modules with important #interview questions at the end of each tutorial along with solutions
If you find the content USEFUL, make sure to give a THUMBS UP :)
** link to the notebook: https://colab.research.google.com/dri...
** pandas doc: https://pandas.pydata.org/docs/refere...
** data source: https://www.kaggle.com/datasets/iabhi...
** getting started guide: https://pandas.pydata.org/docs/gettin...
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Why learn data science??
"Data Science is the sexiest job of 21st century"
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Why learn from datahat??
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learners --- professionals by simplified data science
It provides a platform to learn, create and collaborate helping in the #career #transition to data science, machine learning and data analysis
Understand the broad domain of data science and its related subdomains in machine learning, data analysis, data engineering in a self paced, #structured and #guided learning
* Here are few interesting reads on our blog: / souravagarwal54321
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Additionally, here are few more useful resources for beginners and curious data enthusiasts
1. kaggle: a platform to learn, practice, compete and win cash prizes [https://www.kaggle.com/]
2. paperswithcode: website presenting the latest in machine learning and data science research and the code implementations [https://paperswithcode.com/]
3. google colab: a platform to run code, build machine learning solutions, explore the capabilities of GPU and TPU without any hassle in setting up the environment: [https://colab.research.google.com/]
Remember, "the greatest #investment ever made is investment in self growth and learning"
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