[WIP] The Matplotlib chapter #22
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jni
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Oct 25, 2021
| @@ -6,3 +6,4 @@ plotly | |||
| pandas | |||
| altair | |||
| joblib | |||
| sklearn | |||
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| sklearn | |
| scikit-learn |
jni
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Oct 25, 2021
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| ## Introduction | ||
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| Matplotlib is probably the most widely used Python package for scientific |
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| Matplotlib is probably the most widely used Python package for scientific | |
| Matplotlib is the most widely used Python package for scientific |
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| Matplotlib is probably the most widely used Python package for scientific | ||
| plotting. While it can be used to create animated, and interactive images, its | ||
| main strength is to provide both very quick and easy way to visualize data |
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| main strength is to provide both very quick and easy way to visualize data | |
| main strength is to provide both a very quick and easy way to visualize data |
| from an interactive Python terminal **and** the utilities to create scientific | ||
| publication-quality figures in a wide range of format. | ||
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| In this chapter, we are going create a couple of publication quality plot and |
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| In this chapter, we are going create a couple of publication quality plot and | |
| In this chapter, we are going create a couple of publication quality plots and |
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| should be conveyed by the plot; (2) the target audience; and (3) the support | ||
| of the plot (presentation, website, scientific publication, …). |
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| should be conveyed by the plot; (2) the target audience; and (3) the support | |
| of the plot (presentation, website, scientific publication, …). | |
| should be conveyed by the plot; (2) the target audience; and (3) the medium in | |
| which the plot will appear (presentation, website, scientific publication, …). |
| should be conveyed by the plot; (2) the target audience; and (3) the support | ||
| of the plot (presentation, website, scientific publication, …). | ||
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| [^QA_and_transcriptomic]: Data visualization is very widely used in genomics |
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Should this be a callout box rather than a footnote? Also, can you define root and leaf samples?
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Ok, as in, from an actual plant. 😂 How about, "if you are running an RNA-Seq study on plant data, and you have a mixture of samples from the roots or leaves of the plant, ..."
| Before diving in anything text related with Matplotlib, it's good practice to | ||
| set the figure size. Indeed, in Matplotlib, the fontsize are in points, and | ||
| not relative to the figure size. The figure size is set in inches. Scientific | ||
| publications are typically on A4 papers, while posters are often A0 or A1. |
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| publications are typically on A4 papers, while posters are often A0 or A1. | |
| publications are typically on A4 paper, while posters are often A0 or A1. |
| set the figure size. Indeed, in Matplotlib, the fontsize are in points, and | ||
| not relative to the figure size. The figure size is set in inches. Scientific | ||
| publications are typically on A4 papers, while posters are often A0 or A1. | ||
| Most scientific journals require fontsize no smaller than 8pts. |
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| Most scientific journals require fontsize no smaller than 8pts. | |
| Most scientific journals require fontsize no smaller than 8pt. |
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| | A1 | 594 x 841 mm | 59.4 x 84.1 cm | 23.4 x 33.1 inches | | ||
| | A2 | 420 x 594 mm | 42 x 59.4 cm | 16.5 x 23.4 inches | |
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| | A1 | 594 x 841 mm | 59.4 x 84.1 cm | 23.4 x 33.1 inches | | |
| | A2 | 420 x 594 mm | 42 x 59.4 cm | 16.5 x 23.4 inches | | |
| | A1 | 594 x 841 mm | 23.4 x 33.1 inches | | |
| | A2 | 420 x 594 mm | 16.5 x 23.4 inches | |
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| #### Adding x- and y-labels | ||
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| Let's now set the x-s and y-labels. |
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| Let's now set the x-s and y-labels. | |
| Let's now set the x- and y-labels. |
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| # Let's set the x- and y-labels | ||
| ax.set_xlabel("1st component") | ||
| ax.set_ylabel("1st component") |
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| ax.set_ylabel("1st component") | |
| ax.set_ylabel("2nd component") |
jni
reviewed
Oct 25, 2021
| ax.spines["left"].set_position(("data", 0)) | ||
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| # Now set the axis labels & title | ||
| ax.set_title("Find a meaningful title", fontweight="bold") |
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