Altair and Hvplot Charts

This page is generated from a Jupyter notebook and shows examples of embedding interactive charts produced using Altair and hvPlot.

Example: Measles Incidence in Altair

First, let’s load the data for measles incidence in wide format:

Code

url = "https://raw.githubusercontent.com/MUSA-550-Fall-2023/week-2/main/data/measles_incidence.csv"
data = pd.read_csv(url, skiprows=2, na_values="-")

	YEAR	WEEK	ALABAMA	ALASKA	ARIZONA	ARKANSAS	CALIFORNIA	COLORADO	CONNECTICUT	DELAWARE	...	SOUTH DAKOTA	TENNESSEE	TEXAS	UTAH	VERMONT	VIRGINIA	WASHINGTON	WEST VIRGINIA	WISCONSIN	WYOMING
0	1928	1	3.67	NaN	1.90	4.11	1.38	8.38	4.50	8.58	...	5.69	22.03	1.18	0.4	0.28	NaN	14.83	3.36	1.54	0.91
1	1928	2	6.25	NaN	6.40	9.91	1.80	6.02	9.00	7.30	...	6.57	16.96	0.63	NaN	0.56	NaN	17.34	4.19	0.96	NaN
2	1928	3	7.95	NaN	4.50	11.15	1.31	2.86	8.81	15.88	...	2.04	24.66	0.62	0.2	1.12	NaN	15.67	4.19	4.79	1.36
3	1928	4	12.58	NaN	1.90	13.75	1.87	13.71	10.40	4.29	...	2.19	18.86	0.37	0.2	6.70	NaN	12.77	4.66	1.64	3.64
4	1928	5	8.03	NaN	0.47	20.79	2.38	5.13	16.80	5.58	...	3.94	20.05	1.57	0.4	6.70	NaN	18.83	7.37	2.91	0.91

5 rows × 53 columns

Then, use the pandas.melt() function to convert it to tidy format:

Code

annual = data.drop("WEEK", axis=1)
measles = annual.groupby("YEAR").sum().reset_index()
measles = measles.melt(id_vars="YEAR", var_name="state", value_name="incidence")

	YEAR	state	incidence
0	1928	ALABAMA	334.99
1	1929	ALABAMA	111.93
2	1930	ALABAMA	157.00
3	1931	ALABAMA	337.29
4	1932	ALABAMA	10.21

Finally, load altair:

import altair as alt

And generate our final data viz:

# use a custom color map
colormap = alt.Scale(
    domain=[0, 100, 200, 300, 1000, 3000],
    range=[
        "#F0F8FF",
        "cornflowerblue",
        "mediumseagreen",
        "#FFEE00",
        "darkorange",
        "firebrick",
    ],
    type="sqrt",
)

# Vertical line for vaccination year
threshold = pd.DataFrame([{"threshold": 1963}])

# plot YEAR vs state, colored by incidence
chart = (
    alt.Chart(measles)
    .mark_rect()
    .encode(
        x=alt.X("YEAR:O", axis=alt.Axis(title=None, ticks=False)),
        y=alt.Y("state:N", axis=alt.Axis(title=None, ticks=False)),
        color=alt.Color("incidence:Q", sort="ascending", scale=colormap, legend=None),
        tooltip=["state", "YEAR", "incidence"],
    )
    .properties(width=650, height=500)
)

rule = alt.Chart(threshold).mark_rule(strokeWidth=4).encode(x="threshold:O")

out = chart + rule
out

Example: Measles Incidence in hvplot

Generate the same data viz in hvplot:

# Make the heatmap with hvplot
heatmap = measles.hvplot.heatmap(
    x="YEAR",
    y="state",
    C="incidence", # color each square by the incidence
    reduce_function=np.sum, # sum the incidence for each state/year
    frame_height=450,
    frame_width=600,
    flip_yaxis=True,
    rot=90,
    colorbar=False,
    cmap="viridis",
    xlabel="",
    ylabel="",
)

# Some additional formatting using holoviews 
# For more info: http://holoviews.org/user_guide/Customizing_Plots.html
heatmap = heatmap.redim(state="State", YEAR="Year")
heatmap = heatmap.opts(fontsize={"xticks": 0, "yticks": 6}, toolbar="above")
heatmap