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_episodes/07-visualization-ggplot-python.md

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~~~
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{: .language-python}
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![png](../fig/06_first_plot.png)
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![scatter plot of hindfoot length vs weight with black dots denoting individual sampled animals, showing 4 main clusters of dots in the middle and left middle sides](../fig/06_first_plot.png)
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> ## Challenge - bar chart
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> Working on the `surveys_complete` data set, use the `plot-id` column to
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~~~
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{: .language-python}
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![scatter plot of Hindfoot length vs weight (g) with colors coordinating to specfic species, showing abundance in the mid to lower left side of the plot](../fig/06_color_label_plot.png)
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![png](../fig/06_color_label_plot.png)
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- Defining scale for colors, axes,... For example, a log-version of the x-axis
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could support the interpretation of the lower numbers:
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~~~
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{: .language-python}
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![24 individual scatter plots of Hindfoot length vs weight of species with colors denoting species and numbers above plot representing 1 of the 24 plots, showing trends for each unique plot id studied](../fig/06_facet_all_plot.png)
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![png](../fig/06_facet_all_plot.png)
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The `facet_wrap` geometry extracts plots into an arbitrary number of dimensions
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to allow them to cleanly fit on one page. On the other hand, the `facet_grid`

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