擅长:python、mysql、java
<p>我们想到的一个解决方案是编写一个基于<code>upper</code>和<code>lower bounds</code>查找离群值的函数,然后根据离群值索引对{<cd3>}进行切片</p>
<pre><code>df1 = pd.DataFrame({'wave': [1, 2, 3, 4, 5]})
df2 = pd.DataFrame({'stlines': [0.1, 0.2, 0.3, 0.4, 0.5]})
def outlier(value, upper, lower):
"""
Find outliers based on upper and lower bound
"""
# Check if input value is within bounds
in_bounds = (value <= upper) and (value >= lower)
return in_bounds
# Function finds outliers in wave column of DF1
outlier_index = df1.wave.apply(lambda x: outlier(x, 4, 1))
# Return DF2 without values at outlier index
df2[outlier_index]
# Return DF1 without values at outlier index
df1[outlier_index]
</code></pre>