Differences

This shows you the differences between two versions of the page.

--- other:python:jyp_steps [2019/03/18 14:53] – [Quick Reference] jypeter
+++ other:python:jyp_steps [2019/05/23 16:54] – [Matplotlib] Added ref to subplot_adjust jypeter
@@ Line 187: / Line 187: @@
     - some resources for having multiple plots on the same figure
       * [[https://matplotlib.org/gallery/recipes/create_subplots.html#sphx-glr-gallery-recipes-create-subplots-py|Easily creating subplots]]
+        * [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.subplots_adjust.html|subplots_adjust]] can be used to change the boundaries
       * [[https://matplotlib.org/gallery/index.html#subplots-axes-and-figures|Subplots, axes and figures]] gallery
       * [[https://matplotlib.org/tutorials/intermediate/gridspec.html#sphx-glr-tutorials-intermediate-gridspec-py|Customizing Figure Layouts Using GridSpec and Other Functions]], [[https://matplotlib.org/tutorials/intermediate/constrainedlayout_guide.html|constrained layout]] and [[https://matplotlib.org/tutorials/intermediate/tight_layout_guide.html|tight layout]]
@@ Line 204: / Line 205: @@
   - Read the [[http://www.labri.fr/perso/nrougier/teaching/matplotlib/|Matplotlib tutorial by Nicolas Rougier]]
   - Download the [[http://matplotlib.org/contents.html|pdf version of the manual]]. **Do not print** the 2800+ pages of the manual! Read the beginner's guide (Chapter //FIVE// of //Part II//) and have a super quick look at the table of contents of the whole document.
+==== Useful reference pages ====
+  * [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.plot.html|plot(...)]]: Plot y versus x as lines and/or markers
+  * [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.scatter.html|scatter(...)]]: A scatter plot of y vs x with varying marker size and/or color
+    * The ''plot'' function will be faster for scatterplots where markers don't vary in size or color
+  * [[https://matplotlib.org/api/_as_gen/matplotlib.lines.Line2D.html|line]] parameters
+    * ''linestyle'': ''solid'', ''None'', [[https://matplotlib.org/api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.set_linestyle|other]] ([[https://matplotlib.org/examples/lines_bars_and_markers/line_styles_reference.html|default styles example]], [[https://matplotlib.org/examples/lines_bars_and_markers/linestyles.html|custom styles example]])
+  * [[https://matplotlib.org/api/markers_api.html|marker types]]
+    * ''fillstyle'': ''full'', ''None'', [[https://matplotlib.org/gallery/lines_bars_and_markers/marker_fillstyle_reference.html|other]]
+    * Other attributes: ''markersize'', ''markerfacecolor'' (and ''markerfacecoloralt'' for dual color markers), ''markeredgecolor'', ''markeredgewidth''
+  * [[https://matplotlib.org/api/colors_api.html|colors]]
+    * [[https://matplotlib.org/gallery/color/color_demo.html|color demo]]
+    * [[https://matplotlib.org/examples/color/named_colors.html|named colors]]
+  * [[https://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.legend|legend(...)]] ([[https://matplotlib.org/examples/pylab_examples/legend_demo3.html|legend demo]])
+    * The legend will //show// the lines (or other objects) that were associated with a //label// with the ''label='' keyword when creating/updating a plot
+      * If there are some elements of a plot that you do not want to associate with a legend (e.g. there are several lines with the same color and markers, but you want to plot the legend only once), do not specify a ''label='' keyword for these elements, or add a ''_'' at the front of the label strings
+    * The legend is positioned somewhere (that can be specified) **inside** the plot. In order to place a legend **outside** the plot, use the ''bbox_to_anchor'' parameter
+      * the parameters of ''bbox_to_anchor'' are in normalized coordinates of the current (sub)plot:
+        * ''(0, 0)'' is the lower left corner of the plot, and ''(1, 1)'' the upper right corner
+        * ''legend(... bbox_to_anchor=(1.05, 1.), loc='upper left', ...)'' will put the upper left corner of the legend slightly right (''(1.05, 1.)'') of the upper right corner (''(1, 1)'') of the plot
+      * if the legend is outside of the plot, you have to **explicitly provide enough space for the legend on the page**
+        * e.g. with [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.subplots_adjust.html|subplots_adjust]], ''plt.subplots_adjust(right=0.75)'' will make all the plots use 75% on the left of the page, and leave 25% on the right for the legend
 ==== Misc Matplotlib tricks ====
@@ Line 214: / Line 238: @@
   * [[http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003833|Ten Simple Rules for Better Figures]]
+  * [[https://www.machinelearningplus.com/plots/top-50-matplotlib-visualizations-the-master-plots-python/|Top 50 matplotlib Visualizations]]
   * [[http://seaborn.pydata.org/|Seaborn]] is a library for making attractive and informative statistical graphics in Python, built on top of matplotlib
     * See also: [[https://www.datacamp.com/community/tutorials/seaborn-python-tutorial|
@@ Line 332: / Line 357: @@
   * Python 3 [[https://perso.limsi.fr/pointal/python:abrege|Quick reference]] and [[https://perso.limsi.fr/pointal/python:memento|Cheat sheet]]
-  * [[https://www.datacamp.com/community/blog/jupyter-notebook-cheat-sheet|Jupyter Notebook Cheat Sheet]]
+  * [[https://www.cheatography.com/weidadeyue/cheat-sheets/jupyter-notebook/pdf_bw/|Jupyter Notebook Keyboard Shortcuts]]
 ===== Misc tutorials =====
@@ Line 373: / Line 398: @@
   * [[https://www.datacamp.com/community/tutorials/data-science-python-ide|Top 5 Python IDEs For Data Science]]
   * [[http://noeticforce.com/best-python-ide-for-programmers-windows-and-mac|Python IDE: The10 Best IDEs for Python Programmers]]
+  * [[https://www.techbeamers.com/best-python-ide-python-programming/|Get the Best Python IDE]]
   * [[https://wiki.python.org/moin/IntegratedDevelopmentEnvironments]]