Learn about Python-based data analytics, discover data manipulation and cleaning techniques, explore Jupyter for insights, and gain skills to plot and visualize data effectively.

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In this course, you will get an introduction to Python-based data analytics. You will learn the inner workings of Python to the point where you can confidently find and manipulate data sources and use a Jupyter environment to derive insights from your data.

By the end of this course, you will be able to find and clean data sources, plot your data, and use Python functionalities that show graphs of data.

It’s your all-in-one guide to teaching yourself data analytics in 30 days.

Data Analytics in Python

GDP has no correlation with anxiety disorders.

According to our model, are anxiety disorders more prevalent in higher or lower GDP nations?

According to our model, are anxiety disorders more prevalent in higher or lower GDP nations?

The following image shows
 
<img src="/udata/W5bGx7rl6Z5/image-062.png" height= 360 width=500>

The following image shows
 
<img src="/udata/W5bGx7rl6Z5/image-062.png" height= 360 width=500>

What is the output of the following code?
```
import pandas as pd
import numpy as np
gdp = pd.read_csv('WorldBank_PerCapita_GDP.csv')
anx = pd.read_csv('anxiety.csv')
anx = anx[['Country','Val']]
merged_data_anx = pd.merge(gdp, anx, on='Country')
merged_data_anx = merged_data_anx[['Country', 'Valu\
e', 'Val']]
print (merged_data_anx.head())

What is the output of the following code?
<pre><code>import pandas as pd
import numpy as np
gdp = pd.read_csv('WorldBank_PerCapita_GDP.csv')
anx = pd.read_csv('anxiety.csv')
anx = anx[['Country','Val']]
merged_data_anx = pd.merge(gdp, anx, on='Country')
merged_data_anx = merged_data_anx[['Country', 'Valu\
e', 'Val']]
print (merged_data_anx.head())</code></pre>

What is the output of the following code?
```
import pandas as pd
import numpy as np
anx = pd.read_csv('anxiety.csv')
anx = anx[['Country','Val']]
print (anx.head())

What is the output of the following code?
<pre><code>import pandas as pd
import numpy as np
anx = pd.read_csv('anxiety.csv')
anx = anx[['Country','Val']]
print (anx.head())</code></pre>

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

Before We Begin

Comparing Wages With Consumer Price Index Data

Wages and CPI: Reality Check

Working With Major US Storm Data

Property Rights and Economic Development

How Representative Is Your Government?

Does Wealth Influence The Prevalence Of Mental Illness?

Do Birthdays Make Elite Athletes?

Does Literacy Impact The Income of People

Conclusion

Appendix

Quiz