Learn about querying data; scatter plots; logarithmic plots; and plot marker color and size.
- [Instructor] Plotting two variables together…lets us hypothesize and inspect…possible relations between them.…Do they rise and fall together,…is it possible that the change in one,…is causing the change in the other?…Formally, we say that we would like to explain the variation…in a response variable as a function of the variation…in an explanatory variable.…We'll go back to the Gapminder global dataset,…and first load packages.…
A simple thing to do,…is to plot a variable using the date…as the explanatory variable.…This is known as a time series.…For instance I'll look at a population…of my country of origin, Italy.…I will first down select the data.…In Pandas we plot two variables together,…with plot.scatter.…
And we just give it the two variables.…We see that in this dataset,…points become denser after 1950.…The slope of the plot doesn't change very much,…something like this would be very different for China,…or for India.…Let's try.…
Going back to Italy, let's look at income per person per day…in 2011 equivalent dollars,…
Author
Michele Vallisneri
Released
7/17/2018- Installing and setting up Python
- Importing and cleaning data
- Visualizing data
- Describing distributions and categorical variables
- Using basic statistical inference and modeling techniques
- Bayesian inference
Skill Level Intermediate
Duration
Views
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Introduction
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Welcome1m 9s
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Using the exercise files1m 2s
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1. Installation and Setup
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2. Importing and Cleaning Data
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The structure of data1m 52s
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Create tidy data tables5m 20s
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Introducing pandas7m 28s
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Data cleaning12m 6s
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3. Visualizing and Describing Data
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The power of visualization7m 12s
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Describe distributions5m 3s
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Plot distributions7m 34s
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More quantitative variables7m 58s
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Plot categorical variables4m 30s
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Personal email analytics10m 10s
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4. Introduction to Statistical Inference
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Statistical inference1m 27s
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Confidence intervals9m 30s
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Bootstrapping7m 10s
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Hypothesis testing7m 34s
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5. Introduction to Statistical Modeling
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Statistical modeling1m 35s
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Fitting models to data7m 36s
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Goodness of fit6m 13s
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Cross validation6m 22s
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Logistic regression5m 30s
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Bayesian inference9m 14s
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Conclusion
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Next steps1m 55s
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Video: Plots of two quantitative variables