擅长:python、mysql、java
<p>另一种使用<a href="https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.from_dict.html" rel="nofollow noreferrer">from_dict</a>的方法</p>
<pre><code>d = { '123' : {'name': 'Joe', 'age': '17'},
'888' : {'name': 'Cheryl', 'hometown': 'Liverpool'},
'432' : {'name': 'Raj'}
}
df = pd.DataFrame.from_dict(d, orient = 'index').unstack().reset_index()
df
level_0 level_1 0
0 name 123 Joe
1 name 432 Raj
2 name 888 Cheryl
3 age 123 17
4 age 432 NaN
5 age 888 NaN
6 hometown 123 NaN
7 hometown 432 NaN
8 hometown 888 Liverpool
</code></pre>
<p>如果要删除NaN,只需在语句末尾添加<code>.dropna()</code>。你知道吗</p>
<pre><code>df = pd.DataFrame.from_dict(d, orient = 'index').unstack().reset_index().dropna()
df
level_0 level_1 0
0 name 123 Joe
1 name 432 Raj
2 name 888 Cheryl
3 age 123 17
8 hometown 888 Liverpool
</code></pre>