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"""
china_power_redesigned.py
=========================

A redesign of a dual-axis stacked-area chart from S&P Global's "Look Forward:
Energy Futures" (Feb 2026), showing China's power generation mix and CO2
emissions, 2015-2025.

The original chart tried to show two claims at once:
    (1) electricity demand keeps rising,

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np.random.seed(123456)
N = 100
aim = 0
scale = 0.5
adjusted = []
for i in range(N):
    curr = np.random.randn() * scale + aim
    adjusted.append(curr)
    aim = -curr
non_adjusted = np.random.randn(N)*scale

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from __future__ import print_function
import numpy as np
def asciihist(it, bins=10, minmax=None, str_tag='',
              scale_output=30, generate_only=False, print_function=print):
    """Create an ASCII histogram from an interable of numbers.

    Author: Boris Gorelik boris@gorelik.net. based on  http://econpy.googlecode.com/svn/trunk/pytrix/pytrix.py
    License: MIT
    """
    ret = []

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