擅长:python、mysql、java
<p>pandas函数<code>append</code>对于较大的数据帧来说可能会很慢。相反,我建议将<code>newframes</code>存储在python列表中,而不是使用只附加所有帧一次的<a href="http://pandas.pydata.org/pandas-docs/stable/merging.html" rel="nofollow">concat</a>函数。在</p>
<pre><code>import pandas as pd
def full_data(dataframe):
allframes = []
for i in dataframe.index:
newframe = pd.DataFrame()
newframe['dates'] = pd.date_range(dataframe.iloc[i].start, dataframe.iloc[i].end, freq = 'D')
newframe['name'] = dataframe.iloc[i]['name']
newframe['address'] = dataframe.iloc[i]['address']
allframes.append(newframe)
return concat(allframes)
</code></pre>
<p>注意,这还没有经过测试。在</p>