擅长:python、mysql、java
<p>我认为您可以使用<code>dict</code>来存储所有<code>DataFrames</code>,它是用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.groupby.html" rel="nofollow noreferrer">^{<cd4>}</a>和{a2}创建的<code>dict comprehension</code>:</p>
<pre><code>producs = df['product'].str.split().str[-1]
print (producs)
0 Mask
1 Lotion
2 Shampoo
Name: product, dtype: object
dfs = {i:df.reset_index(drop=True) for i, df in df.groupby(producs)}
print (dfs)
{'Shampoo': day product order
0 2010-01-03 600ml Shampoo 33, 'Mask': day product order
0 2010-01-01 150ml Mask 9, 'Lotion': day product order
0 2010-01-02 230ml Lotion 27}
print (dfs['Shampoo'])
day product order
0 2010-01-03 600ml Shampoo 33
</code></pre>
<p>如果需要删除列<code>product</code>,请使用子集<code>[['day','order']]</code>或{a3}:</p>
^{pr2}$