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Colormaps

Import Colormaps

To import the statworx theme colormaps to a matplotlib, simply run the apply_style functions as shown below. Now you can call these colormaps by their name like their native counterparts. Note that the name of all statworx colormaps start with stwx:.

# mkdocs: render
from statworx_theme import apply_style
apply_style()

List of Available Colormaps

Discrete Maps

# mkdocs: render

plot_color_gradients('Discrete Statworx Themes',
                     ['stwx:standard', 'stwx:alternative', 'stwx:deep'])

Continous Maps

# mkdocs: render
plot_color_gradients('Qualitative Statworx Themes',
                     ['stwx:good2bad', 'stwx:bad2good'])

# mkdocs: render
plot_color_gradients(
    "Fading Statworx Themes", [f"stwx:{c}_fade" for c in ["Bl", "Rd", "Gn", "Yw"]]
)

# mkdocs: render
from itertools import product

color_names = ["Bl", "Rd", "Gn", "Yw"]
plot_color_gradients(
    "Blending Statworx Themes",
    [f"stwx:{c1}{c2}_blend" for (c1, c2) in product(color_names, color_names) if c1 != c2],
)

# mkdocs: render
from itertools import product

color_names = ["Bl", "Rd", "Gn", "Yw"]
plot_color_gradients(
    "Diverging Statworx Themes",
    [f"stwx:{c1}{c2}_diverging" for (c1, c2) in product(color_names, color_names)],
)

# mkdocs: render
from itertools import product

color_names = ["Bl", "Rd", "Gn", "Yw"]
plot_color_gradients(
    "Rising Statworx Themes",
    [f"stwx:{c}_rise" for c in color_names],
)

Usage

# mkdocs: render
import seaborn as sns
import matplotlib.pyplot as plt

# Load the example flights dataset and convert to long-form
flights_long = sns.load_dataset("flights")
flights = flights_long.pivot("month", "year", "passengers")

# Draw a heatmap with the numeric values in each cell
f, ax = plt.subplots(figsize=(9, 6))
sns.heatmap(flights, annot=True, fmt="d", linewidths=.5, ax=ax, cmap="stwx:good2bad")

# mkdocs: render
import seaborn as sns
import matplotlib.pyplot as plt

# Load the example flights dataset and convert to long-form
flights_long = sns.load_dataset("flights")
flights = flights_long.pivot("month", "year", "passengers")

# Draw a heatmap with the numeric values in each cell
f, ax = plt.subplots(figsize=(9, 6))
sns.heatmap(flights, annot=True, fmt="d", linewidths=.5, ax=ax, cmap="stwx:Bl_fade")

# mkdocs: render
import seaborn as sns
import matplotlib.pyplot as plt

# Load the example flights dataset and convert to long-form
flights_long = sns.load_dataset("flights")
flights = flights_long.pivot("month", "year", "passengers")

# Draw a heatmap with the numeric values in each cell
f, ax = plt.subplots(figsize=(9, 6))
sns.heatmap(flights, annot=True, fmt="d", linewidths=.5, ax=ax, cmap="stwx:Rd_rise")
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