<p>您可以使用pandas<a href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.groupby.html" rel="nofollow noreferrer">groupby()</a>函数(和pandas<a href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html" rel="nofollow noreferrer">DataFrames</a>)获得每个类别的平均值</p>
<pre><code>import pandas as pd
df = pd.read_csv( FILE_NAME.csv )
averages_df = df.groupby(by=["Product Category"]).mean()
</code></pre>
<p>这将创建一个数据框,其行数与Product Category的唯一值相同,然后取每个类别剩余列的平均值</p>
<p>如果您的数据如下所示:</p>
<pre><code>>>> df
Product Category Weight Price
0 Fruit 1 2
1 Vegetable 2 3
2 Fruit 3 6
</code></pre>
<p>然后<code>averages_df</code>将如下所示:</p>
<pre><code>>>> averages_df
Weight Price
Product Category
Fruit 2 4
Vegetable 2 3
</code></pre>
<p>要访问特定类别的方法,您可以通过索引查找</p>
<pre><code>>>> averages_df.loc["Fruit"]
Weight 2
Price 4
</code></pre>
<p>要访问特定类别和列的平均值,可以按索引和列查找</p>
<pre><code>>>> averages_df.loc["Fruit","Price"]
4
</code></pre>