Matplotlib
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External
Internal
Overview
Install
pip3 install matplotlib
Visualization Types
Plot
Scatter
Difference between Plot and Scatter
A "plot" expects two X and Y vectors as argument, which are expected to have the same length, and it creates a 2D line that includes the (X,Y) points. The points are connected by line segments.
Visualization Style
The visualization style can be set globally with:
import matplotlib.pyplot as plt
plt.style.use(<style-name>)
where available style names can be obtained with:
import matplotlib.pyplot as plt
print(plt.style.available)
Solarize_Light2
_classic_test_patch
_mpl-gallery
_mpl-gallery-nogrid
bmh
classic
dark_background
fast
fivethirtyeight
ggplot
grayscale
seaborn-v0_8
seaborn-v0_8-bright
seaborn-v0_8-colorblind
seaborn-v0_8-dark
seaborn-v0_8-dark-palette
seaborn-v0_8-darkgrid
seaborn-v0_8-deep
seaborn-v0_8-muted
seaborn-v0_8-notebook
seaborn-v0_8-paper
seaborn-v0_8-pastel
seaborn-v0_8-poster
seaborn-v0_8-talk
seaborn-v0_8-ticks
seaborn-v0_8-white
seaborn-v0_8-whitegrid
tableau-colorblind10
Interesting styles:
- seaborn-v0_8-whitegrid
Otherwise, style elements like axes, gridlines, line color and width can be set up individually.
Color Palette
A list of colors that can be used to change the colors in plots, so they don't look the same. This line pulls the default colors from the style.
color_pal = plt.rcParams["axes.prop_cycle"].by_key()["color"]