Data Analysis with Python Pandas: Practical Exercises Part 1

Welcome to Data Analysis with Python Pandas: Practical Exercises Part 1 of our interview series, where we explore the world of real-world data analysis using Python Pandas. In this session, we delve 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:

1:10 - Display number of rows and columns -df.shape()
1:30 - How to get a short overview of you dataset - df.info()
2:10 - 2:25 - Display Top and Last 10 rows of the dataset - df.head(), df.tail()
2:30 - Combine specific rows into the dataframe and reset the index - concat()
5:10 - Find all the unique “Team column” values in a dataset - unique()
6:08 - Use of nunique
7:42 - Display the number of unique values in a Team column - value_counts()
8:40 - Check the number of Null values in a dataset for one multiple or all columns - isnull().sum()
10:35 - Get the overall info about integer values from the dataframe - df.describe
11:40 - Count the total number of not empty values for each row or column in a dataframe - count()
12:51 - Find the number of times when the Team column is equal to Boston Celtics
14:52 - Find the number of times when the Team column is equal to Boston Celtics with Query method
15:42 - Find it with group by
17:42 - Find it with with str contains by filling the NaN values with blank space


#python #pandas #dataanalysis

Source:
https://github.com/Rruhid/data


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Data Analysis with Python Pandas
Data Analysis
Python Pandas
Real-World Exercises
Data Exercises
Data Interview


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