<p>这可以分两步完成。首先进行外部合并,然后保留重叠的行。在</p>
<pre><code>import pandas as pd
# your data
# ===================================
df
value my_key from_dt to_dt
0 1 a 2007-01-01 2009-02-01
1 2 b 2001-01-01 2011-01-01
2 3 c 2015-01-01 2020-01-01
df2
my_key value2 from_dt to_dt
0 a a1 2007-01-01 2008-01-01
1 a a2 2008-01-01 2010-01-01
2 b b1 2009-01-01 2015-01-01
3 c c1 2011-01-01 2011-12-30
# processing
# ======================================
# outer merge
df_temp = pd.merge(df, df2, on=['my_key'], how='outer')
# just make sure that the columns are in proper datetime type
# you don't have to do this if your data is already in datetime
df_temp.from_dt_x = pd.to_datetime(df_temp.from_dt_x)
df_temp.to_dt_x = pd.to_datetime(df_temp.to_dt_x)
df_temp.from_dt_y = pd.to_datetime(df_temp.from_dt_y)
df_temp.to_dt_y = pd.to_datetime(df_temp.to_dt_y)
value my_key from_dt_x to_dt_x value2 from_dt_y to_dt_y
0 1 a 2007-01-01 2009-02-01 a1 2007-01-01 2008-01-01
1 1 a 2007-01-01 2009-02-01 a2 2008-01-01 2010-01-01
2 2 b 2001-01-01 2011-01-01 b1 2009-01-01 2015-01-01
3 3 c 2015-01-01 2020-01-01 c1 2011-01-01 2011-12-30
# get rows that do overlap
result = df_temp[(df_temp.to_dt_x >= df_temp.from_dt_y) & (df_temp.from_dt_x <= df_temp.to_dt_y)]
value my_key from_dt_x to_dt_x value2 from_dt_y to_dt_y
0 1 a 2007-01-01 2009-02-01 a1 2007-01-01 2008-01-01
1 1 a 2007-01-01 2009-02-01 a2 2008-01-01 2010-01-01
2 2 b 2001-01-01 2011-01-01 b1 2009-01-01 2015-01-01
</code></pre>
<h3>更新:</h3>
^{pr2}$