Remove column name from chart title in sns.relplot and keep only horizontal grid line

Question

I am trying to create a diverging dot plot with python and I am using seaborn relplot to do the small multiples with one of the columns.

The datasouce is MakeoverMonday 2018w18: MOM2018w48

I got this far with this code:

sns.set_style("whitegrid")
g=sns.relplot(x=cost ,y=city, col=item, s=120, size = cost, hue = cost, col_wrap= 2)
sns.despine(left=True, bottom=True)

which generates this:

So, far, so good. Now, I want only horizontal gridlines, sort it and get rid of the column name ('item'=) in the small multiple charts. Any ideas?

This is what I am trying to recreate:

Answer 1

I can get reasonably close by just using Matplotlib (no seaborn). Matplotlib is sometimes a little more low-level, but this also allows a lot of customization to be done.

There's definitely still some hacky-things going on to mimic the appearance of your example image as close as possible. Perhaps there are more elegant ways to get there.

Having a DataFrame structured as:

Creating the plot with:

colors = {"Taxi": "C2", "Club entry": "C0", "Big Mac": "C3"}

fig, axs = plt.subplot_mosaic(
    [["Taxi", "Club entry", "Big Mac"]], figsize=(12, 4.5), sharey=True, sharex=True, 
    facecolor="w", dpi=86,
)
fig.subplots_adjust(left=0, right=1, bottom=0, top=1, wspace=0.1)

for name in axs:
    
    # subset dataframe
    df_subset = df.query(f"Item == '{name}'")
    
    axs[name].set_title(name, size=14, alpha=.5)
    line, = axs[name].plot(
        "Cost", "City", "o", data=df_subset,
        ms=24, color=colors[name],
    )
    
    # add value inside the circle (marker)
    for i, cost_value in enumerate(df_subset["Cost"].to_list()):
        axs[name].text(
            cost_value, i, f"${cost_value:1.0f}", ha="center", va="center",
            weight="bold", color="w", alpha=.8, size=10,
        )        
        
for i, ax in enumerate(axs.values()):
    ax.xaxis.set_major_locator(mpl.ticker.MultipleLocator(10))
    ax.xaxis.set_major_formatter(mpl.ticker.StrMethodFormatter("${x:1.0f}"))
    ax.grid(axis="y", linewidth=3, alpha=0.5)
    ax.grid(axis="x", linewidth=0.5, alpha=0.5)
    ax.tick_params(axis='both', which='both', length=0, labelcolor="#00000077")
    ax.xaxis.set_ticks_position("top")
    
    for sp in ax.spines:
        ax.spines[sp].set_visible(False)
        
    if i == 0: # only applies to the left axis
        ax.set_yticklabels([]) # hide default labels
        ax.yaxis.set_major_locator(mpl.ticker.FixedLocator(range(len(df_subset))))
        
        # add yticklabels manually (for alignment...)
        yticklabels = [(f"{x:<20s}", f"${y:<3.0f}") for x,y in list(df_subset[["City", "Total Cost"]].to_records(index=False))]

        for ypos, (city_name, total_cost) in enumerate(yticklabels):
            # negative x-offset is in units "Total Cost"
            ax.text(-18, ypos, city_name, ha="left", va="center", alpha=.5)
            ax.text(-5, ypos, total_cost, ha="left", va="center", alpha=.9)