pythonmatplotlibmatplotlib-3d

Set aspect ratio in matplotlib 3.8 3D plots

I am trying to plot this: https://100.datavizproject.com/data-type/viz4/

enter image description here

Using matplotlib.

I have got this far:

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import pandas as pd

colors = [ "#2B314D", "#A54836","#5375D4", ]

data = {
    "year": [2004, 2022, 2004, 2022, 2004, 2022],
    "countries" : ["Sweden", "Sweden", "Denmark", "Denmark", "Norway", "Norway"],
    "sites": [13,15,5,8,4,10]
}
df= pd.DataFrame(data)
df['year_lbl'] ="'"+df['year'].astype(str).str[-2:].astype(str)

nr_countries = df.countries.nunique()
nr_years = df.year.nunique()
years = df.year.unique()
x= [1,1,1]
y=[0,0,0]
z= [0,0,0]

dx= [1,1,1]
dy= [1,1,1]

fig = plt.figure(figsize=(15,10))

for i,yrs in zip(range(0,nr_years), years):
    
    # Add the i+1 subplot of the x.shape[0] x 1 grid
    ax = fig.add_subplot(1,nr_years, i+1,  projection='3d')

    temp_df = df[df.year == yrs]
    dz = temp_df.sites.tolist()
    _zpos = z   # the starting zpos for each bar
    for i, c in zip(range(nr_countries), colors):
        ax.bar3d(x,y,_zpos,dx,dy,dz[i],color= c)
        _zpos += np.array(dz[i])  # add the height of each bar to know where to start the next
    ax.set_axis_off()

enter image description here

But I am trying to stretch it, to get the same effect as in the link above but I just cant get it right.

I upgraded to 3.8 matplotlib to use:

ax.set_ylim(0,15)
ax.set_xlim(0,15)
ax.set_zlim(0,25)
ax.set_aspect('equal', adjustable='datalim')

but I dont get the same effect. What I am doing wrong? enter image description here

Solution

  • You don't need to use two separate axes for the bar plot. You can do:

    ...

# width/depth of bars
dx = 2
dy = 2

# seperation between the two bars
separation = 3 * dx

# x and y anchor points of all the bars
xs = [0, 0, 0, separation, separation, separation]
ys = [0, 0, 0, separation / 2, separation / 2, separation / 2]

# bar z-positions and heights
zs = []
dz = []
for year in years:
    sites = df[df["year"] == year].sort_values("countries")["sites"].values
    zp = np.cumsum(sites).tolist()
    zs.extend([0] + zp[: len(zp) - 1])
    dz.extend(sites.tolist())

fig = plt.figure(figsize=(15,10))
ax = fig.add_subplot(1, 1, 1, projection="3d")

ax.bar3d(xs, ys, zs, dx, dy, dz, color=colors + colors)

# add year labels
for i, year in enumerate(years):
    ax.text(xs[i * nr_countries], ys[i * nr_countries], z=-3, s=f"{year}", fontweight="bold", fontsize="large")

ax.set_aspect("equal")
ax.set_axis_off()

    which gives:

    enter image description here

    Note: this was using matplotlib version 3.8.2.