<p>我认为需要使用groupby和连接元组到<code>list</code>的值<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.cut.html" rel="nofollow noreferrer">^{<cd1>}</a>:</p>
<pre><code>print (df1)
Date Articles
0 2010-01-04 ((t, r), (s, q))
1 2010-01-07 ((g, f), (y, l))
2 2010-01-08 ((d, p), (t, o))
3 2010-01-12 ((t, c), (r, p))
b = pd.concat([df2['Date'],
pd.Series(pd.to_datetime(['1970-01-01','2100-01-01']))]).sort_values()
df1['Dates'] = pd.cut(df1['Date'], bins=b, labels=b[1:], right=False)
df3 = (df1.groupby('Dates')['Articles']
.apply(lambda x: [i for s in x for i in s])
.iloc[:-1]
.reset_index())
print (df3)
Dates Articles
0 2010-01-08 [(t, r), (s, q), (g, f), (y, l)]
1 2010-01-15 [(d, p), (t, o), (t, c), (r, p)]
2 2010-01-22 []
3 2010-01-29 []
</code></pre>
<p>Last if want filter out empty<code>lists</code>:</p>
<pre><code>df3 = df3[df3['Articles'].astype(bool)]
print (df3)
Dates Articles
0 2010-01-08 [(t, r), (s, q), (g, f), (y, l)]
1 2010-01-15 [(d, p), (t, o), (t, c), (r, p)]
</code></pre>