<p>给定字典<code>d</code>:</p>
<pre><code>d = {"type":"product","**products**":[{"id":466501,"title":"Nicholas Cole Cellars GraEagle Red Wing","image":"https://spoonacular.com/productImages/466501-312x231.jpg","imageType":"jpg"},{"id":455061,"title":"Wieninger Wiener Gemischter Satz","image":"https://spoonacular.com/productImages/455061-312x231.jpg","imageType":"jpg"},{"id":452162,"title":"The Magnificent Wine Company Steak House","image":"https://spoonacular.com/productImages/452162-312x231.jpg","imageType":"jpg"},{"id":464255,"title":"Chateau Morrisette Black Dog","image":"https://spoonacular.com/productImages/464255-312x231.jpg","imageType":"jpg"},{"id":434441,"title":"Dr. Konstantin Frank Gewurztraminer","image":"https://spoonacular.com/productImages/434441-312x231.jpg","imageType":"jpg"},{"id":451567,"title":"Delectus Dirty Old Dog ( Magnum)","image":"https://spoonacular.com/productImages/451567-312x231.jpg","imageType":"jpg"},{"id":437451,"title":"Bleasdale Frank Potts Red Blend","image":"https://spoonacular.com/productImages/437451-312x231.jpg","imageType":"jpg"},{"id":451606,"title":"Dr. Konstantin Frank Rkatsiteli","image":"https://spoonacular.com/productImages/451606-312x231.jpg","imageType":"jpg"},{"id":440486,"title":"Dog House Checker's Cab","image":"https://spoonacular.com/productImages/440486-312x231.jpg","imageType":"jpg"},{"id":445496,"title":"Dog House Charlie's Chard","image":"https://spoonacular.com/productImages/445496-312x231.jpg","imageType":"jpg"}],"offset":0,"number":10,"totalProducts":7573,"processingTimeMs":380,"expires":1594279471761}
</code></pre>
<p>您可以将所有数据卸载到单个数据帧中:</p>
<pre><code>df = pd.DataFrame.from_dict(d)
df = pd.concat([df.drop(columns = ['**products**']), df['**products**'].apply(pd.Series)], axis = 1)
</code></pre>
<p>输出数据帧结构<code>df.dtypes</code>:</p>
<pre><code>type object
offset int64
number int64
totalProducts int64
processingTimeMs int64
expires int64
id int64
title object
image object
imageType object
dtype: object
</code></pre>
<p>现在只需选择相关列</p>