擅长:python、mysql、java
<p>使用合并</p>
<pre><code># Sample Data
df1 = pd.DataFrame( {'foo': [2,11,18,6,14,12,8,13,7,5]})
df2 = pd.DataFrame({'bar': [2,5,7,8,3],
'date' : [datetime.date(2020, 1, 6)]*5 })
# Merge with left join and filter out required columns
df = df1.merge(df2, how='left', left_on='foo', right_on='bar')[['foo', 'date']]
# populate result based on the missing data
df['result'] = ~result['date'].isnull()
# Finally replace all missing date with the default one you want
df['date'] = df['date'].fillna(datetime.date(2020,8, 24))
print (df)
</code></pre>
<p>输出:</p>
<pre><code> foo date result
0 2 2020-01-06 True
1 11 2020-08-24 False
2 18 2020-08-24 False
3 6 2020-08-24 False
4 14 2020-08-24 False
5 12 2020-08-24 False
6 8 2020-01-06 True
7 13 2020-08-24 False
8 7 2020-01-06 True
9 5 2020-01-06 True
</code></pre>