Real-World Data Analysis with Python Pandas - Interview (Part 8): Exercises and Insights

Welcome to Part 8 of our interview series, where we explore real-world data analysis with Python Pandas. In this session, we dive into practical exercises and gain valuable insights. Whether you're a data enthusiast, analyst, or simply curious about the power of data analysis, you're in for a rewarding experience.

Chapters:
1:20 - Convert date columns to datetime type
2:50 - Calculate the time taken to sell each item
4:10 - Calculate the total quantity sold or the average quantity sold per transaction
5:35 - Filter rows where the time taken to sell is greater than 100 days
6:55 - Group by the purchase month and calculate the total quantity sold per month
10:53 - Bring back date to the original format
12:38 - Convert timedelta to a human-readable format "X days"

#python #ai #bigdata #dataanalysis #datascience #pandas


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Data Analysis
Python Pandas
Real-World Exercises
Data Visualization
Data Exercises
Data Interview
Data Analysis Skills
Data-Driven Decision Making
Data Experts
Python for Data Analysis
Practical Data Analysis
Real-World Data Scenarios
Data Analysis Insights
Data Manipulation
Data Interpretation
Data Visualization Mastery

Data Analysis with Python Pandas: Discover how Python Pandas empowers data manipulation, analysis, and insights.
Real-World Data Exercises: Engage in hands-on exercises to apply your data analysis skills to practical scenarios.
Data Visualization: Understand the art of presenting insights through effective data visualization.
Interview with Data Experts: Learn from experienced data professionals who share their insights and expertise.
Data-Driven Decision Making: Explore how data analysis drives informed decisions in various industries.
Python Pandas and Real-World Insights: Tips and tricks for using Pandas to draw actionable conclusions from data.
Data Analysis Skills Development: A valuable resource for data professionals and learners.
Real-World Data Projects: Gain inspiration from the application of data analysis in real-life situations.

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