擅长:python、mysql、java
<p>一种方法是将<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.floordiv.html" rel="nofollow noreferrer">^{<cd1>}</a>除以<code>0.01</code>,然后再将值除以<code>100</code>:</p>
<pre><code>s.floordiv(0.01).div(100)
0 1.42
1 12.33
2 111.66
3 2.05
dtype: float64
</code></pre>
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<p>它的性能明显优于转换为字符串并提取到小数点后第二位:</p>
<pre><code>s = pd.Series(np.random.randn(1_000_000))
%timeit s.astype(str).str.extract(r'(\d+\.\d{2})')
# 1.76 s ± 42.1 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
%timeit s.floordiv(0.01).div(100)
# 42.1 ms ± 3.08 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)
%timeit s//0.01/100
# 40.5 ms ± 3.31 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)
</code></pre>