How to specify subplots layout with gridspec

I'm trying to use plt.GridSpec() to set up two subplots such that the left one takes up about 67% of the space and the right one takes up 33%.

I looked at the documentation, but I just can't seem to figure out how to set up the indexing--probably due a lack of experience with numpy slicing.

Repeatable Example

%matplotlib inline
import matplotlib.pyplot as plt
import pandas as pd


## Dummy Data
x = [0, 0.03, 0.075, 0.108, 0.16, 0.26, 0.37, 0.49, 0.76, 1.05, 1.64,
    0.015, 0.04, 0.085, 0.11, 0.165, 0.29, 0.37, 0.6, 0.78, 1.1]
y = [16.13, 0.62, 2.15, 41.083, 59.97, 13.30, 7.36, 6.80, 4.97, 3.53, 11.77,
    30.21, 64.47, 57.64, 56.83, 46.69, 4.22, 30.35, 35.12, 5.22, 25.32]
label = ['blue', 'blue', 'blue', 'blue', 'blue', 'blue', 'blue', 'blue', 'blue', 'blue', 'blue',
        'red', 'red', 'red', 'red', 'red', 'red', 'red', 'red', 'red', 'red', 'red']

df = pd.DataFrame(
    list(zip(x, y, label)), 
    columns =['x', 'y', 'label']
    ) 

## Plotting
fig = plt.figure(figsize=([10,8]))
grid = plt.GridSpec(1, 3, wspace=0.4, hspace=0.3)
ax1 = plt.subplot(grid[0, :1])
ax2 = plt.subplot(grid[0, 2], sharey = ax1)

ax1.scatter(x=df.y, y=df.x, color=df.label)

df_red = df[df['label'] == "red"]
df_blue = df[df['label'] == "blue"]
myhist = ax2.hist([df_blue.x, df_red.x],
         density=False,
         edgecolor='black',
         color=['blue', 'red'],
         cumulative=False,
         bins='auto',
         orientation='horizontal',
         stacked=True,
         label=['Blue', 'Red'])

ax1.set_xlabel('length')
ax1.set_ylabel('value')
ax2.set_xlabel('frequency')
ax2.set_ylabel('value')

Current Result

Desired Result
Same plot, just with the left:right ratio at 67% : 33% (so left plot is wider than right plot).

Solution

Here's the small modification that you need to make:

# one position less than 3rd column
ax1 = plt.subplot(grid[0, :-1])