擅长:python、mysql、java
<p>简单的解决方案是提供一个二维数组</p>
<pre><code>df=pd.DataFrame([["XXL", 8, "black", "class 1", 22],
["L", np.nan, "gray", "class 2", 20],
["XL", 10, "blue", "class 2", 19],
["M", np.nan, "orange", "class 1", 17],
["M", 11, "green", "class 3", np.nan],
["M", 7, "red", "class 1", 22]])
df.columns=["size", "price", "color", "class", "boh"]
from sklearn.preprocessing import Imputer
imp=Imputer(missing_values="NaN", strategy="mean" )
imp.fit(df[["price"]])
df["price"]=imp.transform(df[["price"]])
df['boh'] = imp.fit_transform(df[['price']])
</code></pre>
<p>这是你的数据框</p>
<p><a href="https://i.stack.imgur.com/Lh4KW.png" rel="nofollow noreferrer">Cleaned DataFrame</a></p>