Line plots

from plotnine import (
    ggplot,
    aes,
    geom_line,
    facet_wrap,
    labs,
    scale_x_datetime,
    element_text,
    theme_538
)
from plotnine.data import meat

geom_line() connects the dots, and is useful for time series data.

meat.head()

	date	beef	veal	pork	lamb_and_mutton	broilers	other_chicken	turkey
0	1944-01-01	751.0	85.0	1280.0	89.0	NaN	NaN	NaN
1	1944-02-01	713.0	77.0	1169.0	72.0	NaN	NaN	NaN
2	1944-03-01	741.0	90.0	1128.0	75.0	NaN	NaN	NaN
3	1944-04-01	650.0	89.0	978.0	66.0	NaN	NaN	NaN
4	1944-05-01	681.0	106.0	1029.0	78.0	NaN	NaN	NaN

Make it tidy.

meat_long = meat.melt(
    id_vars="date",
    value_vars=["beef", "veal", "pork", "lamb_and_mutton", "broilers", "turkey"],
    var_name="animal",
    value_name="weight"
).dropna()

meat_long.head()

	date	animal	weight
0	1944-01-01	beef	751.0
1	1944-02-01	beef	713.0
2	1944-03-01	beef	741.0
3	1944-04-01	beef	650.0
4	1944-05-01	beef	681.0

First try

p = (
    ggplot(meat_long, aes(x="date", y="weight"))
    + geom_line()
)
p

It looks crowded because each there is more than one monthly entry at each x-point. We can get a single trend line by getting a monthly aggregate of the weights.

meat_long_monthly_agg = meat_long.groupby("date").agg({"weight": "sum"}).reset_index()
meat_long_monthly_agg

	date	weight
0	1944-01-01	2205.0
1	1944-02-01	2031.0
2	1944-03-01	2034.0
3	1944-04-01	1783.0
4	1944-05-01	1894.0
...	...	...
955	2023-08-01	9319.1
956	2023-09-01	8586.1
957	2023-10-01	9452.5
958	2023-11-01	8951.1
959	2023-12-01	8555.1

960 rows × 2 columns

A Single Trend Line

(
    ggplot(meat_long_monthly_agg, aes(x="date", y="weight"))
    + geom_line()
)

Add some style

# Gallery, lines
(
    ggplot(meat_long_monthly_agg, aes(x="date", y="weight"))
    + geom_line()
    # Styling
    + scale_x_datetime(date_breaks="10 years", date_labels="%Y")
    + theme_538()
)

Or we can group by the animals to get a trend line for each animal

Multiple Trend Lines

(
    ggplot(meat_long, aes(x="date", y="weight", group="animal"))
    + geom_line()
    # Styling
    + scale_x_datetime(date_breaks="10 years", date_labels="%Y")
    + theme_538()
)

Make each group be a different color.

# Gallery, lines
(
    ggplot(meat_long, aes(x="date", y="weight", color="animal"))
    + geom_line()
    # Styling
    + scale_x_datetime(date_breaks="10 years", date_labels="%Y")
    + theme_538()
)

A Trend Line Per Facet

Plot each group on a separate panel. The legend is no longer required and we adjust to the smaller panels by reducing the size of the line, size of the text and the number of grid lines.

# Gallery, lines
def titled(strip_title):
    return " ".join(s.title() if s != "and" else s for s in strip_title.split("_"))

(
    ggplot(meat_long, aes("date", "weight", color="animal"))
    + geom_line(size=.5, show_legend=False)
    + facet_wrap("animal", labeller=titled)
    + scale_x_datetime(date_breaks="20 years", date_labels="%Y")
    + labs(
        x="Date",
        y="Weight (million pounds)",
        title="Meat Production"
    )
    + theme_538(base_size=9)
)