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Questions and Answers
What is the primary purpose of the pandas library in Python?
What is the primary purpose of the pandas library in Python?
- To build web applications and APIs
- To perform scientific computing and data visualization
- To provide a fast and flexible way to work with structured (tabular) data (correct)
- To handle parallel computing and distributed systems
Which of the following is the correct way to import the pandas library in Python?
Which of the following is the correct way to import the pandas library in Python?
- import pandas as pd (correct)
- from pandas import DataFrame
- from pandas import *
- import pandas.DataFrame as df
What is the difference between a DataFrame and a Series in pandas?
What is the difference between a DataFrame and a Series in pandas?
- There is no difference; they are interchangeable data structures
- A `DataFrame` is a 2D labeled data structure, while a `Series` is a 1D labeled data structure (correct)
- A `DataFrame` is used for time series data, while a `Series` is used for cross-sectional data
- A `DataFrame` can only contain numerical data, while a `Series` can contain any data type
Which of the following is the correct way to create a Series object in pandas?
Which of the following is the correct way to create a Series object in pandas?
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What is the purpose of the groupby function in pandas?
What is the purpose of the groupby function in pandas?
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Which of the following is the correct way to read a CSV file into a DataFrame in pandas?
Which of the following is the correct way to read a CSV file into a DataFrame in pandas?
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Study Notes
Introduction to Pandas
- Pandas is a Python package providing fast, flexible, and expressive data structures for working with relational or labeled data.
- Aims to be the fundamental high-level building block for doing practical, real-world data analysis in Python.
Installing Pandas
- Binary Installers available at https://pypi.org/project/pandas
Basic Pandas Commands
- Imports necessary commands to start working with Pandas
- Commands include:
Creating Data Structures
- Create Dataframe
- Create DataSeries
- Create Test Objects
Data Operations
- Viewing/Inspecting Data
- Selection
- Data Cleaning
- Filter, Sort, and Groupby
- Join/Combine
- Statistics
Data Management
- Importing Data
- Exporting Data
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