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You have completed Introduction to Data Visualization with Matplotlib!
You have completed Introduction to Data Visualization with Matplotlib!
Preview
Let’s utilize a scatter plot to see what correlations if any, there are between the sepal length and width based on the variety of iris.
Color Dict
colors = {"Iris-setosa": "#2B5B84", "Iris-versicolor": "g", "Iris-virginica": "purple"}
Correlations
- Positive Correlation: as one variable increases so does the other. Height and shoe size are an example; as one's height increases so does the shoe size.
- Negative Correlation: as one variable increases, the other decreases. Time spent studying and time spent on video games are negatively correlated; as your time studying increases, time spent on video games decreases.
- No Correlation: there is no apparent relationship between the variables. Video game scores and shoe size appear to have no correlation; as one increases, the other one is not affected.
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there are between the sepal length and
width, based on the variety of aggregates.
0:00
[SOUND] Recall that scatter plots are used
to show how much one variable is impacted
0:03
by another, or its correlation.
0:07
We use scatter plots to show
relationships between values.
0:09
In this case, our sepal length and width.
0:13
The scatter plot allows us to quickly
visualize the distribution of the data and
0:15
notice any outliers.
0:19
We can see if there’s a positive,
negative, or
0:21
nonexistent correlation between our
data based on the scatter plot results.
0:24
Let's jump back into our Python code and
develop our chart.
0:29
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