from datetime import date
import polars as pl
import plotnine_polars as p9
import socviz_pl as sv
from plotnine_polars import aes5 Climate circles
This chapter adapts Dominic Roye’s climate circles example to plotnine_polars. The data are daily station temperatures for nine US cities, averaged by day of year over 1991-2020. Each line shows the average daily temperature range, while colour marks the daily mean temperature.
Caution
All of the examples on this page require the coord-polar branch of iangow/plotnine. The standard version of plotnine does not include the coord_polar() and coord_radial() functions used here.
meteo_yday = sv.load_data("meteo_yday")
col_temp = [
"#cbebf6", "#a7bfd9", "#8c99bc", "#974ea8", "#830f74",
"#0b144f", "#0e2680", "#223b97", "#1c499a", "#2859a5",
"#1b6aa3", "#1d9bc4", "#1ca4bc", "#64c6c7", "#86cabb",
"#91e0a7", "#c7eebf", "#ebf8da", "#f6fdd1", "#fdeca7",
"#f8da77", "#fcb34d", "#fc8c44", "#f85127", "#f52f26",
"#d10b26", "#9c042a", "#760324", "#18000c",
]
month_breaks = [date(2000, m, 15).timetuple().tm_yday for m in range(1, 13)]
month_labels = ["Jan", "Feb", "Mar", "Apr", "May", "Jun",
"Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
month_grid = pl.DataFrame({
"x": [date(2000, m, 1).timetuple().tm_yday for m in range(1, 13)],
"y": [-10] * 12,
"xend": [date(2000, m, 1).timetuple().tm_yday for m in range(1, 13)],
"yend": [41] * 12,
})
temp_grid = pl.DataFrame({"y": [-10, 0, 10, 20, 30, 40]})
temp_labels = pl.DataFrame({
"x": [366] * 6,
"y": [-10, 0, 10, 20, 30, 40],
"label": ["-10", "0", "10", "20", "30", "40"],
})5.1 One City
The non-polar version is a useful way to read the geometry. The x-axis is day of year, and each vertical line runs from the daily average minimum to the daily average maximum.
ny_city = meteo_yday.filter(pl.col("name") == "NEW YORK")
(
ny_city
.ggplot(aes(x="yd", ymin="tmin", ymax="tmx", color="ta"))
.geom_linerange(size=0.5, alpha=0.7)
.scale_y_continuous(breaks=range(-30, 51, 10), limits=(-11, 42),
expand=(0, 0))
.scale_color_gradientn(colors=col_temp, limits=(-12, 35),
breaks=range(-10, 36, 5))
.scale_x_continuous(breaks=month_breaks, labels=month_labels)
.labs(
title="New York Climate Circle Inputs",
x="Day of year",
y="Temperature (degrees C)",
color="Daily average",
)
.add_theme(figure_size=(8, 3.5))
)
Adding coord_radial() wraps the same daily ranges around the year. The month labels are theta-axis labels, while the temperature axis is drawn inside the circle.
(
ny_city
.ggplot(aes(x="yd", ymin="tmin", ymax="tmx", color="ta"))
.geom_linerange(size=0.5, alpha=0.75)
.scale_y_continuous(breaks=range(-30, 51, 10), limits=(-11, 42),
expand=(0, 0))
.scale_color_gradientn(colors=col_temp, limits=(-12, 35),
breaks=range(-10, 36, 5))
.scale_x_continuous(breaks=month_breaks, labels=month_labels)
.coord_radial(r_axis_inside=True, expand=False,
theta_labels=True, theta_label_pad=6)
.labs(
title="New York Climate Circle",
color="Daily average temperature",
)
.add_theme(
axis_title=p9.element_blank(),
axis_text_x=p9.element_text(size=7),
legend_position="bottom",
figure_size=(5.5, 5.5),
)
)
5.2 Nine Cities
The faceted version adds reference rings and month spokes before drawing the daily ranges. This follows the structure of Roye’s final chart, translated to plotnine_polars and the current coord_radial() argument names.
(
meteo_yday
.ggplot(aes(x="yd", ymin="tmin", ymax="tmx", color="ta"))
.geom_hline(data=temp_grid, mapping=aes(yintercept="y"),
color="white", size=0.35, alpha=0.65,
inherit_aes=False)
.geom_text(data=temp_labels, mapping=aes(x="x", y="y", label="label"),
color="white", size=5, ha="left", inherit_aes=False)
.geom_segment(data=month_grid,
mapping=aes(x="x", y="y", xend="xend", yend="yend"),
color="white", size=0.2, linetype="dashed",
alpha=0.5, inherit_aes=False)
.geom_linerange(size=0.5, alpha=0.75)
.scale_y_continuous(breaks=range(-30, 51, 10), limits=(-15, 41.5),
expand=(0, 0))
.scale_color_gradientn(colors=col_temp, limits=(-12, 35),
breaks=range(-10, 36, 5))
.scale_x_continuous(breaks=month_breaks, labels=month_labels)
.facet_wrap("name", nrow=3)
.coord_radial(r_axis_inside=True, expand=False,
theta_labels=True, theta_label_pad=4)
.labs(
title="Climate Circles",
color="Daily average temperature",
)
.add_theme(
plot_background=p9.element_rect(fill="black"),
panel_background=p9.element_rect(fill="black"),
panel_grid=p9.element_blank(),
axis_title=p9.element_blank(),
axis_text_x=p9.element_text(color="white", size=6),
axis_text_y=p9.element_blank(),
axis_ticks=p9.element_blank(),
legend_position="bottom",
legend_title=p9.element_text(color="white"),
legend_text=p9.element_text(color="white"),
plot_title=p9.element_text(color="white", ha="center", size=18),
strip_text=p9.element_text(color="white", weight="bold", size=9),
figure_size=(8, 9),
)
)