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Data Analytics in Python

1.Before We Begin

What Is This Course About?Storing and Protecting Data

2.Comparing Wages With Consumer Price Index Data

Introduction Working with API Working with CPI and Salary Data Manipulating the CPI Data Series Converting Percentages to CPI Values Merge and Plot Our Data Frames Quiz Challenge 1 - Plot a Simple Bar Graph Solution Review - Plot a Simple Bar Graph

3.Wages and CPI: Reality Check

Confirm the Integrity of Your Data Establish a Historical Context for Your Data Incorporate S&P 500 Quotes Calculate the Rate of Increase for Both CPI and S&P Quiz

4.Working With Major US Storm Data

Working With Major US Storm Data US Hurricane Data: 1851–2019 US Hurricane Data: 1851-2019 (Continued)US Tropical Storm Data: 1851-1965, 1983-2019 US Tropical Storm Data:1851-1965, 1983-2019 (Continued)Quiz Challenge 2 — Plot a Simple Histogram Solution Review - Plot a Simple Histogram Challenge 3 — Scatter Plot Solution Review — Scatter Plot

Project

Time Series Analysis and Visualization Using Python and Plotly

5.Property Rights and Economic Development

How Do You Measure Conditions and Outcomes?Getting the Data and Visualizing Datasets Using Scatter Plots Adding Hover Visibility Adding a Regression Line Other Considerations Quiz Challenge 4 - Plot a Regression Line Graph Solution Review - Plot a Regression Line Graph

6.How Representative Is Your Government?

Scraping Data from a Single Vote Automating Vote Tabulation What Did We Learn?Quiz

7.Does Wealth Influence The Prevalence Of Mental Illness?

Fetching Data and Our Assumptions Plotting the Data Thinking about Our Data Quiz

8.Do Birthdays Make Elite Athletes?

National Hockey League Data Scraping and Hiding How to Visualize the Raw Data Quiz

9.Does Literacy Impact The Income of People

Classifying Incomes of The World Importing and Plotting Literacy Rates of Countries US State Incomes and Literacy Rates Quiz

10.Conclusion

11.Appendix

Data Analytics in Python

Quiz

Attempt the quiz to test what you have learned in this chapter.

We'll cover the following...

Technical Quiz

1.

Which command will display a data frame’s columns along with their current data type?

A.

df.describe

B.

df

C.

df(describe)

D.

df.dtypes

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