Welcome to Part 3 of our interview series, where we continue our exploration of real-world data analysis using Python Pandas. In this session, we dive into hands-on practical exercises and uncover valuable insights. Whether you're a data enthusiast, an analyst, or someone eager to dive into practical data analysis, this session provides a solid foundation.
Chapters:
1:13 - Sort the data frame as per Count column
3:25 - Sort the data frame as per Rate and Count columns (Rate in a descending and Count in a descending order).
5:01 - Find the mean value for each numeric column in a Region column:
6:40 - Display Rate, Count for Asia value in Region column
9:40 - Find all instances where a Region is equal to Asia or Europe.
11:05 - Drop Subregion and Rate column from the dataframe:
12:23 - Drop all rows where Count column is greater than 1000
14:20 - Increase all the values of a year column by one
#python #ai #bigdata #dataanalysis #datascience #pandas
Source:
https://github.com/Rruhid/data
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Data Analysis with Python Pandas
Data Analysis
Python Pandas
Real-World Exercises
Data Exercises
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