Data Visualization Design 4 | Lab: Basic Matplotlib

Series: Data Visualization Design

Data Visualization Design 4 | Lab: Basic Matplotlib

  1. A Matplotlib Template

For all of the matplotlib problems, first of all, we must have this template as our starting point.

2. Common Plots and Commonly Used Parameters

(1) Histogram

ax.hist(seq_1, bins)
  • seq_1: our data
  • bins: it defines the number of equal-width bins in the range.

(2) Scatter

ax.scatter(seq_1, seq_2, marker, s)
  • seq_1: our data 1
  • seq_2: our data 2
  • s: the marker size (not string, this is a common misunderstanding in matplotlib)
  • marker: the symbol of the markers
https://matplotlib.org/3.2.1/api/markers_api.html#module-matplotlib.markers

(3) Bar/Barh

ax.bar(seq_1, seq_2, width)
ax.barh(seq_1, seq_2, width) # horizontal bar
  • seq_1: our data 1
  • seq_2: our data 2
  • width: the width of each bar, by default = .75

(4) Plot

ax.plot(seq_1, seq_2, marker, lw)
  • seq_1: our data 1
  • seq_2: our data 2
  • marker: the symbol of the markers, by default None
  • lw: line width, by default = 1

(5) Boxplot

ax.boxplot(seq_1, showfliers)
  • seq_1: our data
  • showfliters (bool): False means not showing outliers, by default True

(6) Violin Plot

ax.violinplot(seq_1)
  • seq_1: our data

(7) Text

ax.violinplot(x, y, string)
  • x: position x
  • y: position y
  • string: our input string

(8) Fill

ax.fill(seq_1, seq_2, color)
  • seq_1: our data 1
  • seq_2: our data 2
  • color: the fill-in color

(9) Vertical Line

ax.axvline(x, ymin, ymax)
  • x: position x
  • ymin: the minimum value of y
  • ymax: the maximum value of y

(10) Horizontal Line

ax.axhline(y, xmin, xmax)
  • y: position y
  • xmin: the minimum value of x
  • xmax: the maximum value of x

(11) Twin Line Plot

ax_new = ax.twinx()
ax_new.plot(seq_1, seq_2, marker, lw)

3. Global Parameters for Plotting

You can also refer to Line2D properties and Text properties and layout for further details.

  • color: assign the fill-in color
https://matplotlib.org/3.1.0/gallery/color/named_colors.html
  • edgecolor: assign the edge color
  • cmap: set the color map, see this link for more info
  • mec: marker edge color
  • alpha: the transparency
  • ms: marker size
  • label: attach a label and shown in the legend
  • ha: or horizontalalignment, [ 'center' | 'right' | 'left' ]
  • va: or verticalalignment, [ 'center' | 'top' | 'bottom' | 'baseline' ]
  • weight: the font weight, [ 'normal' | 'bold' | 'heavy' | 'light' ]
  • fontname: the font name, i.e. [ 'Times' | 'Arial' | …]
  • fontsize: the font size
  • rotation: rotation for a certain degree
  • position: set the position of the anchor
  • ls: line style, could be set as follows

4. Configure the Axes

(1) Set Axis Color

ax.spines['top'].set_color(color)
ax.spines['right'].set_color(color)
ax.spines['left'].set_color(color)
ax.spines['bottom'].set_color(color)
  • color: the color we want to set

(2) Set Axis Visibility

ax.spines['top'].set_color('None')
ax.spines['right'].set_color('None')
ax.spines['left'].set_color('None')
ax.spines['bottom'].set_color('None')

or,

ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_visible(False)
ax.spines['bottom'].set_visible(False)

(3) Set Axis Bounds

ax.spines['left'].set_bounds(a, b)
ax.spines['bottom'].set_bounds(a, b)
  • a: starting point
  • b: ending point

(4) Set Axis Line Width

ax.spines['left'].set_linewidth(w)
ax.spines['bottom'].set_linewidth(w)
  • w: the width we would set here

(5) Set Axis Range

ax.set_xlim(xmin, xmax)
ax.set_ylim(ymin, ymax)
  • xmin: the minimum value of x
  • xmax: the maximum value of x
  • ymin: the minimum value of y
  • ymax: the maximum value of y

5. Set Ticks and Labels

(1) Set Tick Values

ax.set_xticks(list)
ax.set_yticks(list)
  • list: the list of values we want to set for the ticks

(2) Set Tick Labels

ax.set_xticks(range(len(list)))
ax.set_xticklabels(list)
ax.set_yticks(range(len(list)))
ax.set_yticklabels(list)
  • list: the list of labels we want to set for the ticks

(3) Set Tick Colors

ax.tick_params(axis, colors)
  • axis: choose axis to set, [ 'x' | 'y' | 'both' ]
  • colors: set color

(3) Set 0 to Tick Dash Length

ax.tick_params(axis,length=0)
  • axis: choose axis to set, [ 'x' | 'y' | 'both' ]

(4) Set Legend

plt.legend(loc, bbox_to_anchor)
  • loc: the location of this legend
  • bbox_to_anchor: refer to this link

(5) Set Labels

ax.set_xlabel(string, c)
ax.set_ylabel(string, c)
  • string: the label
  • c: the color

6. Set Annotation

(1) Add Arrow & Text

ax.annotate(string, xy, xytext, arrowprops=dict(arrowstyle="->"))
  • string: the text we want to add
  • xy: tuple, the point that the arrow pointing to
  • xytext: tuple, the position where the text located

(2) Add Triangular Annotation

import matplotlib.patches as patches # for drawing shapes
tria = [x, y, z]
tria = np.array(tria)
wedge = patches.Polygon(tria, closed=True, facecolor='black')
wedge.set_clip_on(False)    # allow to draw outside the axes
ax.add_patch(wedge)
ax.text(a, b, string)
ax.set_ylim(ymin, ymax)   # set the limitation of the y-axis
  • x: the position x of a triangular
  • y: the position y of a triangular
  • z: the position z of a triangular
  • a: the position x of our text
  • b: the position y of our text
  • ymin: the minimum value of y
  • ymax: the maximum value of y

7. Set Title

ax.set_title(string, position, fontname, fontsize, c)
  • string: our title
  • position: the position of this title
  • fontname: set the font name
  • fontsize: set the font size
  • c: the color of the title

8. Matplotlib Cheatsheet

Find them on the GitHub link: https://github.com/matplotlib/cheatsheets