擅长:python、mysql、java
<p>通过协构造函数创建新的数据帧,并通过<a href="http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.concat.html" rel="nofollow noreferrer">^{<cd1>}</a>,最后一次正向填充<code>date</code>值将其添加到原始数据帧:</p>
<pre><code>test = {'a':32, 'b':21, 'c':92}
df1 = pd.DataFrame(list(test.items()), columns=['result','cost'])
df = pd.concat([df, df1], ignore_index=True)
df['date'] = df['date'].ffill()
print (df)
date result cost
0 2021-03-01 a 30
1 2021-03-01 d 35
2 2021-03-01 j 98
3 2021-03-01 b 94
4 2021-03-01 a 32
5 2021-03-01 b 21
6 2021-03-01 c 92
</code></pre>
<p>环路解决方案是可行的,但速度较慢,因此不建议:</p>
<pre><code>for k, v in test.items():
df.loc[len(df), ['result','cost']] = (k, v)
df['date'] = df['date'].ffill()
</code></pre>