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feat(visualizations): clarify exercise 7
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@ -247,9 +247,10 @@ https://plotly.com/python/time-series/
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# Exercise 7: Plotly Box plots
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The goal of this exercise is to learn to use Plotly to plot Box Plots. It is t is a method for graphically depicting groups of numerical data through their quartiles and values as min, max. It allows to compare quickly some variables.
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The goal of this exercise is to learn to use Plotly to plot Box Plots. It is a method for graphically depicting groups of numerical data through their quartiles and values as min, max. It allows comparing quickly some variables.
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Let us generate 3 random arrays from a normal distribution. And for each array add respectively 1, 2 to the normal distribution.
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Generate 3 random arrays from a normal distribution. Keep one as it is and for
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the other two arrays add respectively 1 and 2 to the normal distribution.
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```python
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y0 = np.random.randn(50)
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@ -257,7 +258,7 @@ y1 = np.random.randn(50) + 1 # shift mean
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y2 = np.random.randn(50) + 2
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```
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1. Plot in the same Figure 2 box plots as shown in the image. In this exercise the style is not important.
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1. In the same figure, plot the 3 distributions as box plots as shown in the image. In this exercise the style is not important.
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![alt text][logo_ex7]
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@ -145,29 +145,14 @@ https://matplotlib.org/gallery/api/two_scales.html
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#### Exercise 7: Plotly Box plots
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###### For question 1, does the plot reproduce the plot in the image and respect those criteria? The code below shows a solution.
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###### For question 1, does the plot reproduce the plot in the image as asked in the subject?
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###### Does it have a title?
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###### Does the figure as 3 box plots?
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###### Does it have a legend?
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###### Does the 3 box plots show normal distributions around 0, 1 and 2 respectively?
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Due to the random nature of the distributions, the two graphs do not require a perfect match
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![alt text][logo_ex7]
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[logo_ex7]: ../w1day03_ex7_plot1.png "Box plot ex7"
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```python
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import plotly.graph_objects as go
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import numpy as np
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y0 = np.random.randn(50)
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y1 = np.random.randn(50) + 1 # shift mean
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y2 = np.random.randn(50) + 2
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fig = go.Figure()
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fig.add_trace(go.Box(y=y0, name='Sample A',
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marker_color = 'indianred'))
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fig.add_trace(go.Box(y=y1, name = 'Sample B',
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marker_color = 'lightseagreen'))
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fig.show()
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```
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