Project - 3 (Case Study - 3) Part 1 | Data Analysis With Python Pandas

Dataset Link : [ Ссылка ]
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In this project, we will discuss:
- How to fetch random samples from the Dataset?
- isin
- between
- unique
- dropna
- replace
- duplicated
- drop_duplicates
- astype
- apply
- What is Univariate analysis?
- What is Bivariate analysis?
- Memory Optimization

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Questions :


1.Display Top 10 Rows of The Dataset
2. Check Last 10 Rows of The Dataset
3. Find Shape of Our Dataset (Number of Rows And Number of Columns)
4. Getting Information About Our Dataset Like Total Number Rows, Total Number of Columns, Datatypes of Each Column And Memory Requirement
5. Fetch Random Sample From the Dataset (50%)
6.Check Null Values In The Dataset
7.Perform Data Cleaning [ Replace '?' with NaN ]

8. Drop all The Missing Values
9. Check For Duplicate Data and Drop Them




Github Link: [ Ссылка ]

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