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Module 1 – Importing Data Sets.md

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Module 1 – Importing Data Sets.md

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Learning Objectives

  • Analyze Python data using a dataset
  • Identify three Python libraries and describe their uses
  • Read data using Python's Pandas package
  • Demonstrate how to import and export data in Python

Practice Quiz: Understanding the Data

Question 1: Each column contains a:

  • A. [ ] different used car
  • B. [X] attribute or feature

Practice Quiz: Python Packages for Data Science

Question 1: What description best describes the library Pandas?

  • A. [ ] Includes functions for some advanced math problems as listed in the slide as well as data visualization.
  • B. [X] Offers data structure and tools for effective data manipulation and analysis. It provides fast access to structured data. The primary instrument of Pandas is a two-dimensional table consisting of columns and rows labels which are called a DataFrame. It is designed to provide an easy indexing function.
  • C. [ ] Uses arrays as their inputs and outputs. It can be extended to objects for matrices, and with a little change of coding, developers perform fast array processing.

Practice Quiz: Importing and Exporting Data in Python

Question 1: Some common encodings are ...

  • A. [X] csv
  • B. [X] xlsx
  • C. [ ] Pandas

Question 2: What does the following method do to the dataframe? df : df.head(12)

  • A. [X] Show the first 12 rows of dataframe.
  • B. [ ] Shows the bottom 12 rows of dataframe.

Practice Quiz: Getting Started Analyzing Data in Python

Question 1: To enable a summary of all the columns, what must the parameter include be set to for the method describe?

  • A. [X] df.describe(include=“all”)
  • B. [ ] df.describe(include=“None”)

Lesson summary

In this lesson, you have learned how to:

  • Define the Business Problem: Look at the data and make some high-level decision on what kind of analysis should be done
  • Import and Export Data in Python: How to import data from multiple data sources using the Pandas library and how to export files into different formats.
  • Analyze Data in Python: How to do some introductory analysis in Python using functions like dataframe.head() to view the first few lines of the dataset, dataframe.info() to view the column names and data types.

Importing Data Sets

Importing Data Sets

Graded Quiz: Importing Data Sets

Question 1: What do we want to predict from the dataset?

  • A. [X] price
  • B. [ ] colour
  • C. [ ] make

Question 2: Select the libraries you will use for this course:

  • A. [X] pandas
  • B. [ ] matplotlib
  • C. [ ] scikit-learn

Question 3: What task does the following command perform?

df.to_csv("A.csv")

  • A. [X] Save the dataframe df to a csv file called "A.csv"
  • B. [ ] load the data from a csv file called "A" into a dataframe
  • C. [ ] change the name of the column to "A.csv"

Question 4: Consider the segment of the following dataframe:

1-1

What is the type of the column make?

  • A. [ ] int64
  • B. [ ] float64
  • C. [X] object

Question 5: How would you generate descriptive statistics for all the columns for the dataframe df?

  • A. [ ] df.describe()
  • B. [X] df.describe(include = "all")
  • C. [ ] df.info