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Chapter -9 : Pandas Practice Questions & Materials

Pandas Reading Material - 1

Please download the reading material for Pandas under the resource section
Pandas is a Python library created by Wes McKinney, who built pandas to help work with datasets in Python for his work in finance at his place of employment.
Pandas is "a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language".Pandas stands for ‘panel data’.
Benefit of Pandas Pandas was designed to work with two-dimensional data (similar to Excel spreadsheets). Just as the NumPy library had a built-in data structure called an array with special attributes and methods, the pandas library has a built-in two-dimensional data structure called a DataFrame.
The following concepts will be discussed in the notebook.
Pandas Series
Pandas DataFrames
How To Deal With Missing Data in Pandas
How To Merge DataFrames in Pandas
How To Join DataFrames in Pandas
How To Concatenate DataFrames in Pandas
Common Operations in Pandas
Data Input and Output in Pandas
Data analysis
Statistical Data analysis using pandas
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Pandas Reading Material -1.ipynb
114.8 kB
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Pandas Reading Material - 2

Please download the reading material for Pandas under the resource section
These concepts will be discussed in the following notebook.
- Pandas Series - Pandas Dataframes - Analysis of categorical data - Exploratory data analysis - Visualization - line plot
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Pandas Reading Material - 2.ipynb
491.8 kB
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Pandas Reading Material - 3

Please download the reading material for Pandas under the resource section 
 These concepts will be discussed in the following notebook. 
- Pandas Dataframes - Dividing into numerical and categorical data - Data Cleaning - Statistical Data Analysis - Data Visualization (joint plots) - strip plots - Exploratory Data Analysis - Data Visualization using plotly - Sentiment Analysis on reviews
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Pandas Reading Material - 3.ipynb
817.8 kB
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Pandas Reading Material - 4

Please download the reading material for Pandas under the resource section 
 The following concepts will be discussed in the notebook.
- Pandas input and output - Data cleaning - Dataframe merging - Data visualization - barplot, histogram - Statistical data analysis

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Pandas Reading Material - 4.ipynb
69.3 kB
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Pandas Reading Material - 5

Please download the reading material for Pandas under the resource section 
 The following concepts will be discussed in the notebook.
- Data cleaning - Data Visualization - Exploratory data analysis - Statistical data analysis
File :
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Pandas Reading Material - 5.ipynb
196.3 kB
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Pandas Reading Material - 6


Please download the reading material for Pandas under the resource section 
 The following concepts will be discussed in the notebook.
- Dataframe input  - Exploratory data analysis - Data Visualization - Time series plots
File :
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Pandas Reading Material - 6.ipynb
169.2 kB
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Pandas Reading Material - 6


The following concepts will be discussed in the notebook.
- Dataframe input  - Exploratory data analysis - Data Visualization - Time series plots
File :
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Pandas Reading Material - 6 (1).ipynb
169.2 kB
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Pandas Reading Material - 7

Please download the reading material for Pandas under the resource section 
 The following concepts will be discussed in the notebook.
- Pandas Series - Subsetting the series - creating series from dictionaries - Create dataframe from Series - Data Cleaning - Data Analysis - Statistical Data Analysis
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Pandas Reading Material - 7.ipynb
172.8 kB
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Pandas and NumPy interview Questions

Please download the interview questions and solutions from the resource section.
- This section on Pandas and NumPy Interview Questions covers key questions that are commonly asked during the interview process. You may be new to the interview process, but learning these questions will certainly help you confidently respond to the interviewer and succeed in your next interview.
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NumPy and Pandas Interview Questions.ipynb
119.6 kB
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